From b9be4ffe22b3f6b56c4b7a1df7723252918f84ed Mon Sep 17 00:00:00 2001 From: SOMNATH0904 Date: Fri, 26 Jul 2024 19:37:44 +0530 Subject: [PATCH 1/2] Added IPL Prediction Project --- IPL Prediction/DataSet/IPL IMB381IPL2013.csv | 131 ++ IPL Prediction/MultipleLinearRegression.ipynb | 1112 +++++++++++++++++ IPL Prediction/README.md | 35 + .../Regularisation - RIDGE_LASSO_HYBRID.ipynb | 893 +++++++++++++ 4 files changed, 2171 insertions(+) create mode 100644 IPL Prediction/DataSet/IPL IMB381IPL2013.csv create mode 100644 IPL Prediction/MultipleLinearRegression.ipynb create mode 100644 IPL Prediction/README.md create mode 100644 IPL Prediction/Regularisation - RIDGE_LASSO_HYBRID.ipynb diff --git a/IPL Prediction/DataSet/IPL IMB381IPL2013.csv b/IPL Prediction/DataSet/IPL IMB381IPL2013.csv new file mode 100644 index 000000000..23fbdf886 --- /dev/null +++ b/IPL Prediction/DataSet/IPL IMB381IPL2013.csv @@ -0,0 +1,131 @@ +Sl.NO.,PLAYER NAME,AGE,COUNTRY,TEAM,PLAYING ROLE,T-RUNS,T-WKTS,ODI-RUNS-S,ODI-SR-B,ODI-WKTS,ODI-SR-BL,CAPTAINCY EXP,RUNS-S,HS,AVE,SR-B,SIXERS,RUNS-C,WKTS,AVE-BL,ECON,SR-BL,AUCTION YEAR,BASE PRICE,SOLD PRICE +1,"Abdulla, YA",2,SA,KXIP,Allrounder,0,0,0,0,0,0,0,0,0,0,0,0,307,15,20.47,8.9,13.93,2009,50000,50000 +2,Abdur Razzak,2,BAN,RCB,Bowler,214,18,657,71.41,185,37.6,0,0,0,0,0,0,29,0,0,14.5,0,2008,50000,50000 +3,"Agarkar, AB",2,IND,KKR,Bowler,571,58,1269,80.62,288,32.9,0,167,39,18.56,121.01,5,1059,29,36.52,8.81,24.9,2008,200000,350000 +4,"Ashwin, R",1,IND,CSK,Bowler,284,31,241,84.56,51,36.8,0,58,11,5.8,76.32,0,1125,49,22.96,6.23,22.14,2011,100000,850000 +5,"Badrinath, S",2,IND,CSK,Batsman,63,0,79,45.93,0,0,0,1317,71,32.93,120.71,28,0,0,0,0,0,2011,100000,800000 +6,"Bailey, GJ",2,AUS,CSK,Batsman,0,0,172,72.26,0,0,1,63,48,21,95.45,0,0,0,0,0,0,2009,50000,50000 +7,"Balaji, L",2,IND,CSK+,Bowler,51,27,120,78.94,34,42.5,0,26,15,4.33,72.22,1,1342,52,25.81,7.98,19.4,2011,100000,500000 +8,"Bollinger, DE",2,AUS,CSK,Bowler,54,50,50,92.59,62,31.3,0,21,16,21,165.88,1,693,37,18.73,7.22,15.57,2011,200000,700000 +9,"Botha, J",2,SA,RR,Allrounder,83,17,609,85.77,72,53,1,335,67,30.45,114.73,3,610,19,32.11,6.85,28.11,2011,200000,950000 +10,"Boucher, MV",2,SA,RCB+,W. Keeper,5515,1,4686,84.76,0,0,1,394,50,28.14,127.51,13,0,0,0,0,0,2008,200000,450000 +11,"Bravo, DJ",2,WI,MI+,Allrounder,2200,86,2004,81.39,142,34.1,0,839,70,27.97,127.12,38,1338,47,28.47,8.12,21.11,2011,200000,200000 +12,"Chanderpaul, S",3,WI,RCB,Batsman,9918,9,8778,70.74,14,52.8,1,25,16,8.33,80.64,0,0,0,0,0,0,2008,200000,200000 +13,"Chawla, PP",1,IND,KXIP,Allrounder,5,3,38,65.51,32,41,0,337,24,13.48,113.09,9,1819,73,126.3,38.11,100.2,2008,125000,400000 +14,"de Villiers, AB",2,SA,DD+,W. Keeper,5457,2,4998,93.19,0,0,1,1302,105,34.26,128.53,42,0,0,0,0,0,2008,200000,300000 +15,"Dhawan, S",2,IND,MI+,Batsman,0,0,69,56.09,0,0,0,1540,95,31.43,122.32,36,66,4,16.5,8.25,12,2011,100000,300000 +16,"Dhoni, MS",2,IND,CSK,W. Keeper,3509,0,6773,88.19,1,12,1,1782,70,37.13,136.45,64,0,0,0,0,0,2008,400000,1500000 +17,"Dilshan, TM",2,SL,DD+,Allrounder,4722,32,6455,86.8,67,58.3,1,1077,76,28.34,117.83,24,356,5,71.2,8.07,53,2008,150000,250000 +18,"Dinda, AB",2,IND,KKR+,Bowler,0,0,18,60,5,61.4,0,6,2,1,33.33,0,926,36,25.72,7.29,21.19,2011,100000,375000 +19,"Dravid, RS",3,IND,RCB+,Batsman,13288,1,10889,71.24,4,46.5,1,1703,75,27.92,116.88,23,0,0,0,0,0,2011,400000,500000 +20,"Duminy, J-P",2,SA,MI+,Batsman,654,11,2536,84,25,47.6,0,978,74,36.22,119.27,35,377,10,37.7,7.11,31.8,2009,300000,300000 +21,"Edwards, FH",2,WI,DC,Bowler,380,157,73,45.62,60,35.6,0,4,3,4,80,0,154,5,30.8,6.6,28,2009,150000,150000 +22,"Fernando, CRD",2,SL,MI,Bowler,249,97,239,60.96,187,34.7,0,4,2,0,133.33,0,298,17,17.53,7.64,13.76,2008,150000,150000 +23,"Fleming, SP",3,NZ,CSK,Batsman,7172,0,8037,71.49,1,29,1,196,45,21.77,118.78,3,0,0,0,0,0,2008,350000,350000 +24,"Flintoff, A",2,ENG,CSK,Allrounder,3845,226,3394,88.82,169,33.2,1,62,24,31,116.98,2,105,2,52.5,9.55,33,2009,950000,1550000 +25,"Gambhir, G",2,IND,DD+,Batsman,3712,0,4819,86.17,0,0,1,2065,93,33.31,128.9,32,0,0,0,0,0,2008,220000,725000 +26,"Ganguly, SC",3,IND,KKR+,Batsman,7212,32,11363,73.7,100,45.6,1,1349,91,25.45,106.81,42,363,10,36.3,7.89,27.6,2011,200000,400000 +27,"Gayle, CH",2,WI,KKR+,Allrounder,6373,72,8087,83.95,156,44.4,1,1804,128,50.11,161.79,129,606,13,46.62,8.05,34.85,2008,250000,800000 +28,"Gibbs, HH",3,SA,DC,Batsman,6167,0,8094,83.26,0,0,1,886,69,27.69,109.79,31,0,0,0,0,0,2008,250000,575000 +29,"Gilchrist, AC",3,AUS,DC+,W. Keeper,5570,0,9619,96.94,0,0,1,1775,109,27.73,140.21,86,0,0,0,0,0,2008,300000,700000 +30,"Gony, MS",2,IND,CSK+,Bowler,0,0,0,0,2,39,0,54,15,9,117.39,5,999,30,33.3,8.47,23.6,2011,50000,290000 +31,Harbhajan Singh,2,IND,MI,Bowler,2164,406,1190,80.51,259,46.5,1,430,49,16.54,151.41,22,1469,54,27.2,6.85,23.83,2008,250000,850000 +32,"Harris, RJ",2,AUS,DC+,Bowler,199,46,48,100,44,23.4,0,115,17,10.45,107.48,3,975,44,22.16,7.71,17.27,2011,200000,325000 +33,"Hayden, ML",3,AUS,CSK,Batsman,8625,0,6133,78.96,0,0,0,1107,93,36.9,137.52,44,0,0,0,0,0,2008,225000,375000 +34,"Henderson, T",3,SA,RR,Allrounder,0,0,0,0,0,0,0,11,11,5.5,68.75,1,40,1,40,6.66,36,2009,100000,650000 +35,"Henriques, MC",1,AUS,KKR+,Allrounder,0,0,18,60,1,90,0,49,30,16.33,108.89,1,142,3,47.33,8.82,32.33,2011,50000,50000 +36,"Hodge, BJ",3,AUS,KKR+,Batsman,503,0,575,87.51,1,66,0,1006,73,31.44,121.5,28,300,17,17.65,7.89,13.41,2011,200000,425000 +37,"Hopes, JR",2,AUS,KXIP,Allrounder,0,0,1326,93.71,67,47.1,0,417,71,26.06,136.27,11,548,14,39.14,9.13,25.71,2011,200000,350000 +38,"Hussey, DJ",2,AUS,KKR+,Allrounder,0,0,1488,91.4,18,36.2,0,971,71,26.24,125.78,48,345,6,57.5,8.85,39,2008,100000,625000 +39,"Hussey, MEK",3,AUS,CSK,Batsman,5708,7,5262,86.97,2,117,1,958,116,39.92,120.65,25,0,0,0,0,0,2008,250000,250000 +40,"Jadeja, RA",1,IND,RR+,Allrounder,0,0,860,78.61,57,46.2,0,904,48,23.18,120.86,35,750,26,28.85,7.33,23.65,2011,100000,950000 +41,"Jaffer, W",2,IND,RCB,Allrounder,1944,2,10,43.47,0,0,0,130,50,16.25,107.44,3,0,0,0,0,0,2008,150000,150000 +42,"Jayasuriya, ST",3,SL,MI,Allrounder,6973,98,13430,91.21,323,46,1,768,114,27.43,144.36,39,390,13,30,7.96,22.62,2008,250000,975000 +43,"Jayawardena, DPMD",2,SL,KXIP+,Batsman,10440,6,10596,78.08,7,83.1,1,1471,110,30.65,128.02,33,0,0,0,0,0,2008,250000,475000 +44,"Kaif, M",2,IND,RR+,Batsman,624,0,2753,72.03,0,0,0,259,34,14.39,103.6,6,0,0,0,0,0,2008,125000,675000 +45,"Kallis, JH",3,SA,RCB,Allrounder,12379,276,11498,72.97,270,39.3,1,1965,89,30.7,110.95,37,1713,45,38.07,7.96,28.71,2008,225000,900000 +46,Kamran Akmal,2,PAK,RR,W. Keeper,2648,0,2924,84.31,0,0,0,128,53,25.6,164.1,8,0,0,0,0,0,2008,150000,150000 +47,Kamran Khan,1,IND,RR+,Bowler,0,0,0,0,0,0,0,3,3,3,60,0,224,9,24.89,8.48,17.78,2009,20000,24000 +48,"Karthik, KD",2,IND,DD+,W. Keeper,1000,0,1008,74.5,0,0,0,1231,69,24.14,123.84,28,0,0,0,0,0,2008,200000,525000 +49,"Kartik, M",2,IND,KKR+,Bowler,88,24,126,70.78,37,51.5,0,111,21,18.5,105.71,1,1013,21,48.24,7.02,41.33,2008,200000,425000 +50,"Katich, SM",3,AUS,KXIP,Batsman,4188,21,1324,68.74,0,0,0,241,75,24.1,129.57,8,0,0,0,0,0,2008,200000,200000 +51,"Kohli, V",1,IND,RCB,Batsman,491,0,3590,86.31,2,137,1,1639,73,28.26,119.29,49,345,4,86.25,8.84,58.5,2011,150000,1800000 +52,"Kumar, P",1,IND,RCB+,Bowler,149,27,292,88.21,77,42.1,0,243,34,10.57,114.08,14,1919,53,36.21,7.73,28.11,2011,200000,800000 +53,"Kumble, A",3,IND,RCB,Bowler,2506,619,938,61.06,337,43,1,35,8,11.67,74.47,0,105,2,52.5,9.55,33,2008,250000,500000 +54,"Langeveldt, CK",3,SA,KKR+,Bowler,16,16,73,58.87,100,34.8,0,8,8,4,88.89,1,187,13,14.38,7.19,12,2011,100000,140000 +55,"Laxman, VVS",3,IND,DC+,Batsman,8781,2,2338,71.23,0,0,1,282,52,15.67,105.62,5,0,0,0,0,0,2008,150000,375000 +56,"Lee, B",2,AUS,KXI+,Bowler,1451,310,1100,82.45,377,29.2,0,103,25,11.44,121.18,6,1009,21,48.05,7.56,38.24,2008,300000,900000 +57,"Maharoof, MF",2,SL,DD,Allrounder,556,25,1042,84.44,133,33.3,0,177,39,17.7,143.9,9,520,27,19.26,7.43,15.56,2008,150000,225000 +58,"Malinga, SL",2,SL,MI,Bowler,275,101,327,73.81,185,31.1,0,64,17,5.82,100,4,1381,83,16.64,6.36,15.69,2008,200000,350000 +59,"Mascarenhas, AD",2,ENG,RR+,Allrounder,0,0,245,95.33,13,63.2,0,74,27,8.22,101.37,1,331,19,17.42,7.01,14.95,2011,100000,100000 +60,"Mathews, AD",1,SL,KKR+,Allrounder,1219,7,1447,82.59,42,43,0,376,65,25.07,123.28,12,537,15,35.8,8.2,26.33,2011,300000,950000 +61,"McCullum, BB",2,NZ,KKR+,W. Keeper,3763,0,4511,89.62,0,0,1,1233,158,28.02,123.42,48,0,0,0,0,0,2008,175000,700000 +62,"McDonald, AB",2,AUS,DD+,Allrounder,107,9,0,0,0,0,0,123,33,30.75,125.51,4,244,10,24.4,8.41,17.4,2011,50000,80000 +63,"McGrath, GD",3,AUS,DD,Bowler,641,563,115,48.72,381,34,0,4,4,4,80,0,357,12,29.75,6.61,27,2008,350000,350000 +64,Misbah-ul-Haq,3,PAK,RCB,Batsman,2173,0,2763,75.1,0,0,1,117,47,16.71,144.44,6,0,0,0,0,0,2010,100000,100000 +65,"Mishra, A",2,IND,DD+,Bowler,392,43,5,27.77,19,40.1,0,186,31,10.94,102.2,3,1530,74,20.68,7.11,17.46,2011,100000,300000 +66,"Mithun, A",1,IND,RCB,Bowler,120,9,51,92.72,3,60,0,32,11,8,133.33,1,435,6,72.5,9.89,44,2011,100000,260000 +67,Mohammad Asif,2,PAK,DD,Bowler,141,106,34,34,46,42.1,0,3,3,1.5,50,0,296,8,37,9.25,24,2008,225000,650000 +68,"Morkel, JA",2,SA,CSK,Allrounder,58,1,782,100.25,50,41.4,0,781,71,24.41,146.25,45,1899,69,27.52,8.25,20.01,2008,225000,675000 +69,"Morkel, M",2,SA,RR+,Bowler,555,139,117,75.97,94,28.5,0,60,16,10,111.11,2,884,38,23.26,7.37,18.95,2011,100000,475000 +70,"Muralitharan, M",3,SL,CSK+,Bowler,1261,800,674,77.56,534,35.2,0,20,6,3.33,66.67,0,1395,57,24.47,6.49,22.63,2008,250000,600000 +71,"Nannes, DP",3,AUS,DD+,Bowler,0,0,1,50,1,42,0,4,3,4,30.77,0,627,24,26.13,7.17,21.92,2011,200000,650000 +72,"Nayar, AM",2,IND,MI+,Allrounder,0,0,0,0,0,0,0,563,35,19.41,123.19,19,263,7,37.57,8.74,25.86,2011,50000,800000 +73,"Nehra, A",2,IND,DD+,Bowler,77,44,141,57.31,157,36.6,0,38,22,19,82.61,1,1192,48,24.83,7.57,19.73,2011,200000,850000 +74,"Noffke, AA",2,AUS,RCB,Allrounder,0,0,0,0,1,54,0,9,9,9,90,0,40,1,40,10,24,2010,20000,20000 +75,"Ntini, M",2,SA,CSK,Bowler,699,390,199,66.77,266,32.6,0,11,11,11,61.11,0,242,7,34.57,6.91,30,2008,200000,200000 +76,"Ojha, NV",2,IND,RR+,W. Keeper,0,0,1,14.28,0,0,0,960,94,22.33,117.94,50,0,0,0,0,0,2011,100000,270000 +77,"Ojha, PP",1,IND,DC+,Bowler,70,62,41,43.61,20,41.7,0,10,3,1,30.3,0,1548,69,22.43,7.16,18.8,2011,200000,500000 +78,"Oram, JDP",2,NZ,CSK+,Allrounder,1780,60,2377,87.16,168,39.7,0,106,41,13.25,98.15,5,327,9,36.33,9.26,23.67,2008,200000,675000 +79,Pankaj Singh,2,IND,RCB+,Bowler,0,0,3,100,0,0,0,7,4,3.5,58.33,0,468,11,42.55,9.36,27.27,2011,50000,95000 +80,"Patel, MM",2,IND,RR+,Bowler,60,35,74,66.07,86,36.6,0,39,23,7.8,235.49,0,1504,70,21.49,7.39,17.47,2008,100000,275000 +81,"Patel, PA",2,IND,CSK+,W. Keeper,683,0,736,76.5,0,0,0,912,57,20.27,107.29,13,0,0,0,0,0,2008,150000,325000 +82,"Pathan, IK",2,IND,KXIP+,Allrounder,1105,100,1468,78.96,165,34,0,929,60,23.82,128.31,34,1975,66,29.92,7.74,23.23,2008,200000,925000 +83,"Pathan, YK",2,IND,RR+,Allrounder,0,0,810,113.6,33,45.1,0,1488,100,25.66,149.25,81,1139,36,31.64,7.2,26.36,2008,100000,475000 +84,"Pietersen, KP",2,ENG,RCB+,Batsman,6654,5,4184,86.76,7,57.1,1,634,103,42.27,141.2,30,215,7,30.71,7.41,24.86,2009,1350000,1550000 +85,"Pollock, SM",3,SA,MI,Allrounder,3781,421,3519,86.69,393,39.9,1,147,33,18.37,132.43,8,301,11,27.36,6.54,25,2008,200000,550000 +86,"Pomersbach, LA",2,AUS,KXIP+,Batsman,0,0,0,0,0,0,0,244,79,27.11,130.48,12,0,0,0,0,0,2011,20000,50000 +87,"Ponting, RT",3,AUS,KKR,Batsman,13218,5,13704,80.39,3,50,1,39,20,9.75,73.58,1,0,0,0,0,0,2008,335000,400000 +88,"Powar, RR",2,IND,KXIP+,Bowler,13,6,163,62.69,34,45.1,0,67,28,22.33,104.69,1,527,13,40.54,7.42,32.77,2008,150000,170000 +89,"Raina, SK",1,IND,CSK,Batsman,710,13,3525,92.71,16,61.9,0,2254,98,33.64,139.39,97,678,20,33.9,7.05,28.9,2008,125000,650000 +90,"Ryder, JD",2,NZ,RCB+,Allrounder,1269,5,1100,89.72,11,34.8,0,604,86,21.57,131.88,19,303,8,37.88,7.73,29.5,2009,100000,160000 +91,"Saha, WP",2,IND,KKR+,W. Keeper,74,0,4,80,0,0,0,372,59,28.62,128.28,16,0,0,0,0,0,2011,100000,100000 +92,"Sangakkara, KC",2,SL,KXIP+,W. 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SR-B SIXERS RUNS-C WKTS AVE-BL ECON \\\n", + "125 0 0.00 ... 125.64 2 0 0 0.00 0.00 \n", + "126 6814 75.78 ... 42.85 0 0 0 0.00 0.00 \n", + "127 8051 87.58 ... 131.88 67 569 23 24.74 7.02 \n", + "128 790 73.55 ... 91.67 1 1783 65 27.43 7.75 \n", + "129 343 95.81 ... 122.22 0 99 2 49.50 9.00 \n", + "\n", + " SR-BL AUCTION YEAR BASE PRICE SOLD PRICE \n", + "125 0.00 2010 50000 750000 \n", + "126 0.00 2008 225000 225000 \n", + "127 21.13 2011 400000 1800000 \n", + "128 21.26 2008 200000 450000 \n", + "129 33.00 2008 100000 110000 \n", + "\n", + "[5 rows x 26 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.tail()" + ] + }, + { + "cell_type": "markdown", + "id": "c9d05b17", + "metadata": {}, + "source": [ + "###### To print information about Data-Frame" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "940ec227", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 130 entries, 0 to 129\n", + "Data columns (total 26 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 Sl.NO. 130 non-null int64 \n", + " 1 PLAYER NAME 130 non-null object \n", + " 2 AGE 130 non-null int64 \n", + " 3 COUNTRY 130 non-null object \n", + " 4 TEAM 130 non-null object \n", + " 5 PLAYING ROLE 130 non-null object \n", + " 6 T-RUNS 130 non-null int64 \n", + " 7 T-WKTS 130 non-null int64 \n", + " 8 ODI-RUNS-S 130 non-null int64 \n", + " 9 ODI-SR-B 130 non-null float64\n", + " 10 ODI-WKTS 130 non-null int64 \n", + " 11 ODI-SR-BL 130 non-null float64\n", + " 12 CAPTAINCY EXP 130 non-null int64 \n", + " 13 RUNS-S 130 non-null int64 \n", + " 14 HS 130 non-null int64 \n", + " 15 AVE 130 non-null float64\n", + " 16 SR-B 130 non-null float64\n", + " 17 SIXERS 130 non-null int64 \n", + " 18 RUNS-C 130 non-null int64 \n", + " 19 WKTS 130 non-null int64 \n", + " 20 AVE-BL 130 non-null float64\n", + " 21 ECON 130 non-null float64\n", + " 22 SR-BL 130 non-null float64\n", + " 23 AUCTION YEAR 130 non-null int64 \n", + " 24 BASE PRICE 130 non-null int64 \n", + " 25 SOLD PRICE 130 non-null int64 \n", + "dtypes: float64(7), int64(15), object(4)\n", + "memory usage: 26.5+ KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "markdown", + "id": "b328cb0b", + "metadata": {}, + "source": [ + "###### Display all columns" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "8f579d11", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['Sl.NO.', 'PLAYER NAME', 'AGE', 'COUNTRY', 'TEAM', 'PLAYING ROLE',\n", + " 'T-RUNS', 'T-WKTS', 'ODI-RUNS-S', 'ODI-SR-B', 'ODI-WKTS', 'ODI-SR-BL',\n", + " 'CAPTAINCY EXP', 'RUNS-S', 'HS', 'AVE', 'SR-B', 'SIXERS', 'RUNS-C',\n", + " 'WKTS', 'AVE-BL', 'ECON', 'SR-BL', 'AUCTION YEAR', 'BASE PRICE',\n", + " 'SOLD PRICE'],\n", + " dtype='object')" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.columns" + ] + }, + { + "cell_type": "markdown", + "id": "2fb63646", + "metadata": {}, + "source": [ + "###### Defining X features for these columns" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "f8b671be", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['Sl.NO.', 'PLAYER NAME', 'AGE', 'COUNTRY', 'TEAM', 'PLAYING ROLE',\n", + " 'T-RUNS', 'T-WKTS', 'ODI-RUNS-S', 'ODI-SR-B', 'ODI-WKTS', 'ODI-SR-BL',\n", + " 'CAPTAINCY EXP', 'RUNS-S', 'HS', 'AVE', 'SR-B', 'SIXERS', 'RUNS-C',\n", + " 'WKTS', 'AVE-BL', 'ECON', 'SR-BL', 'AUCTION YEAR', 'BASE PRICE',\n", + " 'SOLD PRICE'],\n", + " dtype='object')" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "X_Features = df.columns\n", + "X_Features" + ] + }, + { + "cell_type": "markdown", + "id": "2043d653", + "metadata": {}, + "source": [ + "###### Filtering required columns for X_Feature" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "934d0c76", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "20" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "X_Features = ['AGE', 'COUNTRY', 'PLAYING ROLE',\n", + " 'T-RUNS', 'T-WKTS', 'ODI-RUNS-S', 'ODI-SR-B', 'ODI-WKTS', 'ODI-SR-BL',\n", + " 'CAPTAINCY EXP', 'RUNS-S', 'HS', 'AVE', 'SR-B', 'SIXERS', 'RUNS-C',\n", + " 'WKTS', 'AVE-BL', 'ECON', 'SR-BL']\n", + "len(X_Features) # To check no. of columns filtered out" + ] + }, + { + "cell_type": "markdown", + "id": "ad51bb8c", + "metadata": {}, + "source": [ + "###### To check all posible roles defined in 'PLAYING ROLE'" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "537d833c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Allrounder', 'Bowler', 'Batsman', 'W. Keeper'], dtype=object)" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['PLAYING ROLE'].unique()" + ] + }, + { + "cell_type": "markdown", + "id": "344b9e9c", + "metadata": {}, + "source": [ + "###### get_dummies(): Convert categorical variable into dummy/indicator variables." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "0de296fe", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Model: OLS Adj. R-squared: 0.362
Dependent Variable: SOLD PRICE AIC: 2965.2841
Date: 2022-03-18 21:17 BIC: 3049.9046
No. Observations: 104 Log-Likelihood: -1450.6
Df Model: 31 F-statistic: 2.883
Df Residuals: 72 Prob (F-statistic): 0.000114
R-squared: 0.554 Scale: 1.1034e+11
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Coef. Std.Err. t P>|t| [0.025 0.975]
const 375827.1991 228849.9306 1.6422 0.1049 -80376.7996 832031.1978
T-RUNS -53.7890 32.7172 -1.6441 0.1045 -119.0096 11.4316
T-WKTS -132.5967 609.7525 -0.2175 0.8285 -1348.1162 1082.9228
ODI-RUNS-S 57.9600 31.5071 1.8396 0.0700 -4.8482 120.7681
ODI-SR-B -524.1450 1576.6368 -0.3324 0.7405 -3667.1130 2618.8231
ODI-WKTS 815.3944 832.3883 0.9796 0.3306 -843.9413 2474.7301
ODI-SR-BL -773.3092 1536.3334 -0.5033 0.6163 -3835.9338 2289.3154
RUNS-S 114.7205 173.3088 0.6619 0.5101 -230.7643 460.2054
HS -5516.3354 2586.3277 -2.1329 0.0363 -10672.0855 -360.5853
AVE 21560.2760 7774.2419 2.7733 0.0071 6062.6080 37057.9439
SR-B -1324.7218 1373.1303 -0.9647 0.3379 -4062.0071 1412.5635
SIXERS 4264.1001 4089.6000 1.0427 0.3006 -3888.3685 12416.5687
RUNS-C 69.8250 297.6697 0.2346 0.8152 -523.5687 663.2187
WKTS 3075.2422 7262.4452 0.4234 0.6732 -11402.1778 17552.6622
AVE-BL 5182.9335 10230.1581 0.5066 0.6140 -15210.5140 25576.3810
ECON -6820.7781 13109.3693 -0.5203 0.6045 -32953.8282 19312.2721
SR-BL -7658.8094 14041.8735 -0.5454 0.5871 -35650.7726 20333.1539
AGE_2 -230767.6463 114117.2005 -2.0222 0.0469 -458256.1279 -3279.1648
AGE_3 -216827.0808 152246.6232 -1.4242 0.1587 -520325.1772 86671.0155
COUNTRY_BAN -122103.5196 438719.2796 -0.2783 0.7816 -996674.4194 752467.3801
COUNTRY_ENG 672410.7654 238386.2220 2.8207 0.0062 197196.5172 1147625.0135
COUNTRY_IND 155306.4011 126316.3449 1.2295 0.2229 -96500.6302 407113.4325
COUNTRY_NZ 194218.9120 173491.9293 1.1195 0.2667 -151630.9280 540068.7521
COUNTRY_PAK 75921.7670 193463.5545 0.3924 0.6959 -309740.7804 461584.3143
COUNTRY_SA 64283.3894 144587.6773 0.4446 0.6579 -223946.8775 352513.6563
COUNTRY_SL 17360.1530 176333.7497 0.0985 0.9218 -334154.7526 368875.0586
COUNTRY_WI 10607.7792 230686.7892 0.0460 0.9635 -449257.9303 470473.4887
COUNTRY_ZIM -145494.4793 401505.2815 -0.3624 0.7181 -945880.6296 654891.6710
PLAYING ROLE_Batsman 75724.7643 150250.0240 0.5040 0.6158 -223793.1844 375242.7130
PLAYING ROLE_Bowler 15395.8752 126308.1272 0.1219 0.9033 -236394.7744 267186.5249
PLAYING ROLE_W. Keeper -71358.6280 213585.7444 -0.3341 0.7393 -497134.0278 354416.7718
CAPTAINCY EXP_1 164113.3972 123430.6353 1.3296 0.1878 -81941.0772 410167.8716
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Omnibus: 0.891 Durbin-Watson: 2.244
Prob(Omnibus): 0.640 Jarque-Bera (JB): 0.638
Skew: 0.190 Prob(JB): 0.727
Kurtosis: 3.059 Condition No.: 84116
" + ], + "text/plain": [ + "\n", + "\"\"\"\n", + " Results: Ordinary least squares\n", + "========================================================================================\n", + "Model: OLS Adj. R-squared: 0.362 \n", + "Dependent Variable: SOLD PRICE AIC: 2965.2841 \n", + "Date: 2022-03-18 21:17 BIC: 3049.9046 \n", + "No. Observations: 104 Log-Likelihood: -1450.6 \n", + "Df Model: 31 F-statistic: 2.883 \n", + "Df Residuals: 72 Prob (F-statistic): 0.000114 \n", + "R-squared: 0.554 Scale: 1.1034e+11\n", + "----------------------------------------------------------------------------------------\n", + " Coef. Std.Err. t P>|t| [0.025 0.975] \n", + "----------------------------------------------------------------------------------------\n", + "const 375827.1991 228849.9306 1.6422 0.1049 -80376.7996 832031.1978\n", + "T-RUNS -53.7890 32.7172 -1.6441 0.1045 -119.0096 11.4316\n", + "T-WKTS -132.5967 609.7525 -0.2175 0.8285 -1348.1162 1082.9228\n", + "ODI-RUNS-S 57.9600 31.5071 1.8396 0.0700 -4.8482 120.7681\n", + "ODI-SR-B -524.1450 1576.6368 -0.3324 0.7405 -3667.1130 2618.8231\n", + "ODI-WKTS 815.3944 832.3883 0.9796 0.3306 -843.9413 2474.7301\n", + "ODI-SR-BL -773.3092 1536.3334 -0.5033 0.6163 -3835.9338 2289.3154\n", + "RUNS-S 114.7205 173.3088 0.6619 0.5101 -230.7643 460.2054\n", + "HS -5516.3354 2586.3277 -2.1329 0.0363 -10672.0855 -360.5853\n", + "AVE 21560.2760 7774.2419 2.7733 0.0071 6062.6080 37057.9439\n", + "SR-B -1324.7218 1373.1303 -0.9647 0.3379 -4062.0071 1412.5635\n", + "SIXERS 4264.1001 4089.6000 1.0427 0.3006 -3888.3685 12416.5687\n", + "RUNS-C 69.8250 297.6697 0.2346 0.8152 -523.5687 663.2187\n", + "WKTS 3075.2422 7262.4452 0.4234 0.6732 -11402.1778 17552.6622\n", + "AVE-BL 5182.9335 10230.1581 0.5066 0.6140 -15210.5140 25576.3810\n", + "ECON -6820.7781 13109.3693 -0.5203 0.6045 -32953.8282 19312.2721\n", + "SR-BL -7658.8094 14041.8735 -0.5454 0.5871 -35650.7726 20333.1539\n", + "AGE_2 -230767.6463 114117.2005 -2.0222 0.0469 -458256.1279 -3279.1648\n", + "AGE_3 -216827.0808 152246.6232 -1.4242 0.1587 -520325.1772 86671.0155\n", + "COUNTRY_BAN -122103.5196 438719.2796 -0.2783 0.7816 -996674.4194 752467.3801\n", + "COUNTRY_ENG 672410.7654 238386.2220 2.8207 0.0062 197196.5172 1147625.0135\n", + "COUNTRY_IND 155306.4011 126316.3449 1.2295 0.2229 -96500.6302 407113.4325\n", + "COUNTRY_NZ 194218.9120 173491.9293 1.1195 0.2667 -151630.9280 540068.7521\n", + "COUNTRY_PAK 75921.7670 193463.5545 0.3924 0.6959 -309740.7804 461584.3143\n", + "COUNTRY_SA 64283.3894 144587.6773 0.4446 0.6579 -223946.8775 352513.6563\n", + "COUNTRY_SL 17360.1530 176333.7497 0.0985 0.9218 -334154.7526 368875.0586\n", + "COUNTRY_WI 10607.7792 230686.7892 0.0460 0.9635 -449257.9303 470473.4887\n", + "COUNTRY_ZIM -145494.4793 401505.2815 -0.3624 0.7181 -945880.6296 654891.6710\n", + "PLAYING ROLE_Batsman 75724.7643 150250.0240 0.5040 0.6158 -223793.1844 375242.7130\n", + "PLAYING ROLE_Bowler 15395.8752 126308.1272 0.1219 0.9033 -236394.7744 267186.5249\n", + "PLAYING ROLE_W. Keeper -71358.6280 213585.7444 -0.3341 0.7393 -497134.0278 354416.7718\n", + "CAPTAINCY EXP_1 164113.3972 123430.6353 1.3296 0.1878 -81941.0772 410167.8716\n", + "----------------------------------------------------------------------------------------\n", + "Omnibus: 0.891 Durbin-Watson: 2.244\n", + "Prob(Omnibus): 0.640 Jarque-Bera (JB): 0.638\n", + "Skew: 0.190 Prob(JB): 0.727\n", + "Kurtosis: 3.059 Condition No.: 84116\n", + "========================================================================================\n", + "* The condition number is large (8e+04). This might indicate strong\n", + "multicollinearity or other numerical problems.\n", + "\"\"\"" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ipl_model = sm.OLS(train_Y, train_X).fit()\n", + "ipl_model.summary2() # This would full summary of models" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/IPL Prediction/README.md b/IPL Prediction/README.md new file mode 100644 index 000000000..c5884680f --- /dev/null +++ b/IPL Prediction/README.md @@ -0,0 +1,35 @@ +# Predictive Model of IPL 2013 DataSet + +![](https://img.shields.io/badge/Programming_Language-Python-blue.svg) +![](https://img.shields.io/badge/Main_Tool_Used-Jupyter_Notebook-orange.svg) +![](https://img.shields.io/badge/Status-Complete-green.svg) + +## Algorithm Applied: +- Multiple Linear Regression +- Regularisation using Lasso Regression + +## Description: +This project aims to leverage machine learning techniques to predict the outcomes of Indian Premier League (IPL) matches. By utilizing historical IPL data, the project implements various predictive models to forecast match results based on key factors such as team performance, player statistics, and match conditions. The project involves data preprocessing, feature engineering, and model selection to enhance prediction accuracy. It provides a comprehensive guide for intermediate-level enthusiasts to understand and apply machine learning algorithms in sports analytics, making it a valuable resource for those looking to explore the intersection of data science and cricket. + +## Use Cases: +1. Predict Match Outcomes: Forecast IPL match winners. +2. Analyze Team Performance: Evaluate team strengths and weaknesses. +3. Assess Player Contributions: Predict individual player performance. +4. Enhance Betting Strategies: Inform betting decisions with data-driven insights. +5. Improve Fantasy Leagues: Aid in fantasy league team selections. +6. Boost Fan Engagement: Provide predictive analytics for fans. +7. Support Media Analysis: Help commentators and analysts with predictions. +8. Guide Team Strategies: Assist IPL teams in strategic planning. +9. Optimize Sponsorships: Inform sponsors for targeted promotions. + +## Modules used: + - ![NumPy](https://img.shields.io/badge/numpy-%23013243.svg?style=for-the-badge&logo=numpy&logoColor=white) + - ![Pandas](https://img.shields.io/badge/pandas-%23150458.svg?style=for-the-badge&logo=pandas&logoColor=white) + - ![scikit-learn](https://img.shields.io/badge/scikit--learn-%23F7931E.svg?style=for-the-badge&logo=scikit-learn&logoColor=white) + +## Result: +- Multiple Linear Regression (R2 Score = 0.552) +- Regularisation using Lasso Regression (R2 Score for Test = 0.67 & Train = 0.793) + +## Conclusion: +Using Multiple Linear Regression we got a poor model, but applying Lasso Regression regularisation we have made better model. \ No newline at end of file diff --git a/IPL Prediction/Regularisation - RIDGE_LASSO_HYBRID.ipynb b/IPL Prediction/Regularisation - RIDGE_LASSO_HYBRID.ipynb new file mode 100644 index 000000000..9ddc80ce4 --- /dev/null +++ b/IPL Prediction/Regularisation - RIDGE_LASSO_HYBRID.ipynb @@ -0,0 +1,893 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "e12109b8", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "91228bbd", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Sl.NO.PLAYER NAMEAGECOUNTRYTEAMPLAYING ROLET-RUNST-WKTSODI-RUNS-SODI-SR-B...SR-BSIXERSRUNS-CWKTSAVE-BLECONSR-BLAUCTION YEARBASE PRICESOLD PRICE
01Abdulla, YA2SAKXIPAllrounder0000.00...0.0003071520.478.9013.9320095000050000
12Abdur Razzak2BANRCBBowler2141865771.41...0.0002900.0014.500.0020085000050000
23Agarkar, AB2INDKKRBowler57158126980.62...121.01510592936.528.8124.902008200000350000
34Ashwin, R1INDCSKBowler2843124184.56...76.32011254922.966.2322.142011100000850000
45Badrinath, S2INDCSKBatsman6307945.93...120.7128000.000.000.002011100000800000
\n", + "

5 rows × 26 columns

\n", + "
" + ], + "text/plain": [ + " Sl.NO. PLAYER NAME AGE COUNTRY TEAM PLAYING ROLE T-RUNS T-WKTS \\\n", + "0 1 Abdulla, YA 2 SA KXIP Allrounder 0 0 \n", + "1 2 Abdur Razzak 2 BAN RCB Bowler 214 18 \n", + "2 3 Agarkar, AB 2 IND KKR Bowler 571 58 \n", + "3 4 Ashwin, R 1 IND CSK Bowler 284 31 \n", + "4 5 Badrinath, S 2 IND CSK Batsman 63 0 \n", + "\n", + " ODI-RUNS-S ODI-SR-B ... SR-B SIXERS RUNS-C WKTS AVE-BL ECON \\\n", + "0 0 0.00 ... 0.00 0 307 15 20.47 8.90 \n", + "1 657 71.41 ... 0.00 0 29 0 0.00 14.50 \n", + "2 1269 80.62 ... 121.01 5 1059 29 36.52 8.81 \n", + "3 241 84.56 ... 76.32 0 1125 49 22.96 6.23 \n", + "4 79 45.93 ... 120.71 28 0 0 0.00 0.00 \n", + "\n", + " SR-BL AUCTION YEAR BASE PRICE SOLD PRICE \n", + "0 13.93 2009 50000 50000 \n", + "1 0.00 2008 50000 50000 \n", + "2 24.90 2008 200000 350000 \n", + "3 22.14 2011 100000 850000 \n", + "4 0.00 2011 100000 800000 \n", + "\n", + "[5 rows x 26 columns]" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_csv('./DataSet/IPL IMB381IPL2013.csv')\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "16d74c2e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['Sl.NO.', 'PLAYER NAME', 'AGE', 'COUNTRY', 'TEAM', 'PLAYING ROLE',\n", + " 'T-RUNS', 'T-WKTS', 'ODI-RUNS-S', 'ODI-SR-B', 'ODI-WKTS', 'ODI-SR-BL',\n", + " 'CAPTAINCY EXP', 'RUNS-S', 'HS', 'AVE', 'SR-B', 'SIXERS', 'RUNS-C',\n", + " 'WKTS', 'AVE-BL', 'ECON', 'SR-BL', 'AUCTION YEAR', 'BASE PRICE',\n", + " 'SOLD PRICE'],\n", + " dtype='object')" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "a5de09de", + "metadata": {}, + "outputs": [], + "source": [ + "x_Features = ['AGE', 'COUNTRY', 'PLAYING ROLE',\n", + " 'T-RUNS', 'T-WKTS', 'ODI-RUNS-S', 'ODI-SR-B', 'ODI-WKTS', 'ODI-SR-BL',\n", + " 'CAPTAINCY EXP', 'RUNS-S', 'HS', 'AVE', 'SR-B', 'SIXERS', 'RUNS-C',\n", + " 'WKTS', 'AVE-BL', 'ECON', 'SR-BL']" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "4f9424a4", + "metadata": {}, + "outputs": [], + "source": [ + "categorical_features = ['AGE','COUNTRY','PLAYING ROLE','CAPTAINCY EXP']" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a06e4ad8", + "metadata": {}, + "outputs": [], + "source": [ + "encoded_df = pd.get_dummies(df[x_Features],columns=categorical_features, drop_first=True) # Merging" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "2e11c17a", + "metadata": {}, + "outputs": [], + "source": [ + "X = encoded_df\n", + "Y = df['SOLD PRICE']" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "8946460c", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.preprocessing import StandardScaler" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "81239dff", + "metadata": {}, + "outputs": [], + "source": [ + "x_scaler = StandardScaler()\n", + "x_scaled = x_scaler.fit_transform(X)\n", + "Y = (Y-Y.mean())/Y.std()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "b16910de", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "x_train, x_test, y_train, y_test = train_test_split(x_scaled,Y,test_size=0.2,random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "e34d51a6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression()" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.linear_model import LinearRegression\n", + "linreg = LinearRegression()\n", + "linreg.fit(x_train,y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "79635a8a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-0.43539611, -0.04632556, 0.50840867, -0.03323988, 0.2220377 ,\n", + " -0.05065703, 0.17282657, -0.49173336, 0.58571405, -0.11654753,\n", + " 0.24880095, 0.09546057, 0.16428731, 0.26400753, -0.08253341,\n", + " -0.28643889, -0.26842214, -0.21910913, -0.02622351, 0.24817898,\n", + " 0.18760332, 0.10776084, 0.04737488, 0.05191335, 0.01235245,\n", + " 0.00547115, -0.03124706, 0.08530192, 0.01790803, -0.05077454,\n", + " 0.18745577])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "linreg.coef_" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "8683553f", + "metadata": {}, + "outputs": [], + "source": [ + "columns_coef_df = pd.DataFrame({'columns':encoded_df.columns,'coef':linreg.coef_})" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "31b3a596", + "metadata": {}, + "outputs": [], + "source": [ + "sorted_coed_vals = columns_coef_df.sort_values('coef',ascending=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "2c19fe73", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'Features')" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(8,6))\n", + "sns.barplot(x='coef',y='columns',data=sorted_coed_vals)\n", + "plt.xlabel('Coefficients from Linear Regression')\n", + "plt.ylabel('Features')" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "3e7204ae", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn import metrics\n", + "def get_train_test_rmse(model):\n", + " y_train_pred = model.predict(x_train)\n", + " rmse_train = round(np.sqrt(metrics.mean_squared_error(y_train,y_train_pred)),3)\n", + " y_test_pred = model.predict(x_test)\n", + " rmse_test = round(np.sqrt(metrics.mean_squared_error(y_test,y_test_pred)),3)\n", + " print('Train: ',rmse_train,'Test: ',rmse_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "bfbf86d3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train: 0.679 Test: 0.749\n" + ] + } + ], + "source": [ + "get_train_test_rmse(linreg)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "ba8a5e37", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train: 0.68 Test: 0.724\n" + ] + } + ], + "source": [ + "from sklearn.linear_model import Ridge\n", + "ridge = Ridge(alpha=1,max_iter=500)\n", + "ridge.fit(x_train,y_train)\n", + "get_train_test_rmse(ridge)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "a1a8c4fb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train: 0.682 Test: 0.706\n" + ] + } + ], + "source": [ + "ridge = Ridge(alpha=2,max_iter=1000)\n", + "ridge.fit(x_train,y_train)\n", + "get_train_test_rmse(ridge)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "bcfd584c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train: 0.688 Test: 0.698\n" + ] + } + ], + "source": [ + "from sklearn.linear_model import Lasso\n", + "lasso = Lasso(alpha=0.01, max_iter=500)\n", + "lasso.fit(x_train,y_train)\n", + "get_train_test_rmse(lasso)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "bcfda52f", + "metadata": {}, + "outputs": [], + "source": [ + "lasso_coef_df = pd.DataFrame({'columns':encoded_df.columns,'coef':lasso.coef_})" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "6fc58630", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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16AGE_2-0.202695
17AGE_3-0.177818
18COUNTRY_BAN-0.023023
19COUNTRY_ENG0.219205
20COUNTRY_IND0.191417
21COUNTRY_NZ0.063061
22COUNTRY_PAK0.030018
23COUNTRY_SA0.012654
24COUNTRY_SL-0.001749
25COUNTRY_WI-0.021617
26COUNTRY_ZIM-0.025943
27PLAYING ROLE_Batsman0.057139
28PLAYING ROLE_Bowler0.000000
29PLAYING ROLE_W. Keeper-0.048160
30CAPTAINCY EXP_10.158808
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" + ], + "text/plain": [ + " columns coef\n", + "1 T-WKTS -0.0\n", + "3 ODI-SR-B -0.0\n", + "13 AVE-BL -0.0\n", + "28 PLAYING ROLE_Bowler 0.0" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lasso_coef_df[lasso_coef_df.coef==0]" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "cef5380c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train: 0.793 Test: 0.67\n" + ] + } + ], + "source": [ + "from sklearn.linear_model import ElasticNet\n", + "enet = ElasticNet(alpha=1.10,l1_ratio=0.001,max_iter=500)\n", + "enet.fit(x_train,y_train)\n", + "get_train_test_rmse(enet)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From b5ec680f6db5d27c9b08b3660f52ec96f4e4c857 Mon Sep 17 00:00:00 2001 From: SOMNATH0904 Date: Sat, 27 Jul 2024 08:31:34 +0530 Subject: [PATCH 2/2] Added Predictive Traffic Analysis Project --- Predictive Traffic Analysis/README.md | 44 + .../Traffic Forecast.ipynb | 1572 ++ Predictive Traffic Analysis/Traffic data.csv | 18289 ++++++++++++++++ 3 files changed, 19905 insertions(+) create mode 100644 Predictive Traffic Analysis/README.md create mode 100644 Predictive Traffic Analysis/Traffic Forecast.ipynb create mode 100644 Predictive Traffic Analysis/Traffic data.csv diff --git a/Predictive Traffic Analysis/README.md b/Predictive Traffic Analysis/README.md new file mode 100644 index 000000000..8d354ceac --- /dev/null +++ b/Predictive Traffic Analysis/README.md @@ -0,0 +1,44 @@ +# Predictive Traffic Analysis + + +# Dataset Information + +Investors are considering making an investment in a new form of transportation - JetRail. JetRail uses Jet propulsion technology to run rails and move people at a high speed! While JetRail has mastered the technology and they hold the patent for their product, the investment would only make sense, if they can get more than 1 Million monthly users with in next 18 months. + +You need to help Unicorn ventures with the decision. They usually invest in B2C start-ups less than 4 years old looking for pre-series A funding. In order to help Unicorn Ventures in their decision, you need to forecast the traffic on JetRail for the next 7 months. + + +# Attribute Information: + +Datetime - Date and time of the day \ +Count - Count of the vehicle + + +# Libraries + +
  • pandas +
  • matplotlib +
  • seaborn +
  • scikit-learn + +# Algorithms + +
  • FBProphet + + + # Description + This project involves using machine learning techniques to predict traffic patterns. This project applies time series analysis methods to historical traffic data to forecast future traffic conditions. The objective is to provide accurate traffic predictions, which can be beneficial for urban planning, traffic management, and reducing congestion. The project includes data preprocessing, model selection, and evaluation to ensure reliable and robust forecasting results. + +# Use Cases +1. Optimize traffic signals. +2. Reroute vehicles. +3. Adjust public transport schedules. +4. Enhance public transport reliability. +5. Plan emergency service routes. +6. Reduce emergency response times. +7. Optimize delivery routes. +8. Avoid logistics delays. +9. Manage traffic for events. +10. Prevent traffic jams. +11. Suggest optimal travel times. +12. Recommend best routes for commuters. diff --git a/Predictive Traffic Analysis/Traffic Forecast.ipynb b/Predictive Traffic Analysis/Traffic Forecast.ipynb new file mode 100644 index 000000000..219448ffc --- /dev/null +++ b/Predictive Traffic Analysis/Traffic Forecast.ipynb @@ -0,0 +1,1572 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Dataset Information\n", + "\n", + "Investors are considering making an investment in a new form of transportation - JetRail. JetRail uses Jet propulsion technology to run rails and move people at a high speed! While JetRail has mastered the technology and they hold the patent for their product, the investment would only make sense, if they can get more than 1 Million monthly users with in next 18 months.\n", + " \n", + "You need to help Unicorn ventures with the decision. They usually invest in B2C start-ups less than 4 years old looking for pre-series A funding. In order to help Unicorn Ventures in their decision, you need to forecast the traffic on JetRail for the next 7 months." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Import modules" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "from fbprophet import Prophet" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# !pip install fbprophet\n", + "# install visual c++ - visual studio\n", + "# if you face errors - use conda install" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Loading the dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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values\n", + "df.isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 18288 entries, 0 to 18287\n", + "Data columns (total 3 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 ID 18288 non-null int64 \n", + " 1 Datetime 18288 non-null object\n", + " 2 Count 18288 non-null int64 \n", + "dtypes: int64(2), object(1)\n", + "memory usage: 428.8+ KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 18288 entries, 0 to 18287\n", + "Data columns (total 3 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 ID 18288 non-null int64 \n", + " 1 Datetime 18288 non-null datetime64[ns]\n", + " 2 Count 18288 non-null int64 \n", + "dtypes: datetime64[ns](1), int64(2)\n", + "memory usage: 428.8 KB\n" + ] + } + ], + "source": [ + "# convert object to datetime datatype\n", + "df['Datetime'] = pd.to_datetime(df['Datetime'], format='%d-%m-%Y %H:%M')\n", + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
    " + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# EDA\n", + "plt.figure(figsize=(10,7))\n", + "plt.plot(df['Datetime'], df['Count'])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Format data for the model" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
    \n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
    y
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    " + ], + "text/plain": [ + " ds trend yhat_lower yhat_upper trend_lower trend_upper \\\n", + "0 2012-08-25 -473.732066 -1734.877065 163.221651 -473.732066 -473.732066 \n", + "1 2012-08-26 -466.733663 -1855.111354 -6.945309 -466.733663 -466.733663 \n", + "2 2012-08-27 -459.735259 -411.374536 1478.193805 -459.735259 -459.735259 \n", + "3 2012-08-28 -452.736856 -493.053438 1453.702595 -452.736856 -452.736856 \n", + "4 2012-08-29 -445.738452 -474.329272 1523.918170 -445.738452 -445.738452 \n", + "\n", + " additive_terms additive_terms_lower additive_terms_upper weekly \\\n", + "0 -341.012799 -341.012799 -341.012799 -846.187838 \n", + "1 -457.255955 -457.255955 -457.255955 -967.168356 \n", + "2 944.458519 944.458519 944.458519 431.253528 \n", + "3 954.762245 954.762245 954.762245 439.591890 \n", + "4 915.693928 915.693928 915.693928 399.762294 \n", + "\n", + " weekly_lower weekly_upper yearly yearly_lower yearly_upper \\\n", + "0 -846.187838 -846.187838 505.175040 505.175040 505.175040 \n", + "1 -967.168356 -967.168356 509.912400 509.912400 509.912400 \n", + "2 431.253528 431.253528 513.204990 513.204990 513.204990 \n", + "3 439.591890 439.591890 515.170355 515.170355 515.170355 \n", + "4 399.762294 399.762294 515.931634 515.931634 515.931634 \n", + "\n", + " multiplicative_terms multiplicative_terms_lower \\\n", + "0 0.0 0.0 \n", + "1 0.0 0.0 \n", + "2 0.0 0.0 \n", + "3 0.0 0.0 \n", + "4 0.0 0.0 \n", + "\n", + " multiplicative_terms_upper yhat \n", + "0 0.0 -814.744865 \n", + "1 0.0 -923.989618 \n", + "2 0.0 484.723259 \n", + "3 0.0 502.025389 \n", + "4 0.0 469.955476 " + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "forecast = model.predict(future)\n", + "forecast.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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    " + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "model.plot_components(forecast)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "60" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pred = forecast.iloc[-60:, :]\n", + "len(pred)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# test results\n", + "plt.figure(figsize=(10,7))\n", + "plt.plot(test['ds'], test['y'])\n", + "plt.plot(pred['ds'], pred['yhat'], color='red')\n", + "plt.plot(pred['ds'], pred['yhat_lower'], color='green')\n", + "plt.plot(pred['ds'], pred['yhat_upper'], color='orange')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# input data\n", + "plt.plot(df['ds'], df['y'])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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    " + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# forecast data\n", + "plt.plot(forecast['ds'], forecast['yhat'])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n" + ] + }, + { + "data": { + "text/html": [ + "
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    22012-08-27-655.533980-802.8014391564.897491-655.533980-655.5339801007.3485551007.3485551007.348555457.582428457.582428457.582428549.766127549.766127549.7661270.00.00.0351.814576
    32012-08-28-647.495037-659.5670981653.180897-647.495037-647.4950371143.9493981143.9493981143.949398608.387591608.387591608.387591535.561807535.561807535.5618070.00.00.0496.454361
    42012-08-29-639.456095-792.4638591661.049202-639.456095-639.4560951077.0938911077.0938911077.093891556.941854556.941854556.941854520.152037520.152037520.1520370.00.00.0437.637796
    \n", + "
    " + ], + "text/plain": [ + " ds trend yhat_lower yhat_upper trend_lower trend_upper \\\n", + "0 2012-08-25 -671.611865 -2309.461301 177.595130 -671.611865 -671.611865 \n", + "1 2012-08-26 -663.572922 -2419.779673 -159.032282 -663.572922 -663.572922 \n", + "2 2012-08-27 -655.533980 -802.801439 1564.897491 -655.533980 -655.533980 \n", + "3 2012-08-28 -647.495037 -659.567098 1653.180897 -647.495037 -647.495037 \n", + "4 2012-08-29 -639.456095 -792.463859 1661.049202 -639.456095 -639.456095 \n", + "\n", + " additive_terms additive_terms_lower additive_terms_upper weekly \\\n", + "0 -424.000456 -424.000456 -424.000456 -995.245768 \n", + "1 -582.367949 -582.367949 -582.367949 -1144.299997 \n", + "2 1007.348555 1007.348555 1007.348555 457.582428 \n", + "3 1143.949398 1143.949398 1143.949398 608.387591 \n", + "4 1077.093891 1077.093891 1077.093891 556.941854 \n", + "\n", + " weekly_lower weekly_upper yearly yearly_lower yearly_upper \\\n", + "0 -995.245768 -995.245768 571.245311 571.245311 571.245311 \n", + "1 -1144.299997 -1144.299997 561.932049 561.932049 561.932049 \n", + "2 457.582428 457.582428 549.766127 549.766127 549.766127 \n", + "3 608.387591 608.387591 535.561807 535.561807 535.561807 \n", + "4 556.941854 556.941854 520.152037 520.152037 520.152037 \n", + "\n", + " multiplicative_terms multiplicative_terms_lower \\\n", + "0 0.0 0.0 \n", + "1 0.0 0.0 \n", + "2 0.0 0.0 \n", + "3 0.0 0.0 \n", + "4 0.0 0.0 \n", + "\n", + " multiplicative_terms_upper yhat \n", + "0 0.0 -1095.612321 \n", + "1 0.0 -1245.940871 \n", + "2 0.0 351.814576 \n", + "3 0.0 496.454361 \n", + "4 0.0 437.637796 " + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model = Prophet(yearly_seasonality=True, seasonality_prior_scale=0.9)\n", + "model.fit(df)\n", + "future = model.make_future_dataframe(periods=200)\n", + "forecast = model.predict(future)\n", + "forecast.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# forecast data\n", + "plt.plot(forecast['ds'], forecast['yhat'])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Predictive Traffic Analysis/Traffic data.csv b/Predictive Traffic Analysis/Traffic data.csv new file mode 100644 index 000000000..106a77ce2 --- /dev/null +++ b/Predictive Traffic Analysis/Traffic data.csv @@ -0,0 +1,18289 @@ 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