Machine Learning IBM Final Project

In this notebook, you will practice all the classification algorithms that we have learned in this course.

Below, is where we are going to use the classification algorithms to create a model based on our training data and evaluate our testing data using evaluation metrics learned in the course.

We will use some of the algorithms taught in the course, specifically:

1. Linear Regression
2. KNN
3. Decision Trees
4. Logistic Regression
5. SVM

We will evaluate our models using:

1. Accuracy Score
2. Jaccard Index
3. F1-Score
4. LogLoss
5. Mean Absolute Error
6. Mean Squared Error
7. R2-Score

Finally, you will use your models to generate the report at the end.

The original source of the data is Australian Government's Bureau of Meteorology and the latest data can be gathered from http://www.bom.gov.au/climate/dwo/.

The dataset to be used has extra columns like 'RainToday' and our target is 'RainTomorrow', which was gathered from the Rattle at https://bitbucket.org/kayontoga/rattle/src/master/data/weatherAUS.RData

This dataset contains observations of weather metrics for each day from 2008 to 2017. The weatherAUS.csv dataset includes the following fields:

Field	Description	Unit	Type
Date	Date of the Observation in YYYY-MM-DD	Date	object
Location	Location of the Observation	Location	object
MinTemp	Minimum temperature	Celsius	float
MaxTemp	Maximum temperature	Celsius	float
Rainfall	Amount of rainfall	Millimeters	float
Evaporation	Amount of evaporation	Millimeters	float
Sunshine	Amount of bright sunshine	hours	float
WindGustDir	Direction of the strongest gust	Compass Points	object
WindGustSpeed	Speed of the strongest gust	Kilometers/Hour	object
WindDir9am	Wind direction averaged of 10 minutes prior to 9am	Compass Points	object
WindDir3pm	Wind direction averaged of 10 minutes prior to 3pm	Compass Points	object
WindSpeed9am	Wind speed averaged of 10 minutes prior to 9am	Kilometers/Hour	float
WindSpeed3pm	Wind speed averaged of 10 minutes prior to 3pm	Kilometers/Hour	float
Humidity9am	Humidity at 9am	Percent	float
Humidity3pm	Humidity at 3pm	Percent	float
Pressure9am	Atmospheric pressure reduced to mean sea level at 9am	Hectopascal	float
Pressure3pm	Atmospheric pressure reduced to mean sea level at 3pm	Hectopascal	float
Cloud9am	Fraction of the sky obscured by cloud at 9am	Eights	float
Cloud3pm	Fraction of the sky obscured by cloud at 3pm	Eights	float
Temp9am	Temperature at 9am	Celsius	float
Temp3pm	Temperature at 3pm	Celsius	float
RainToday	If there was rain today	Yes/No	object
RainTomorrow (Target)	If there is rain tomorrow	Yes/No	float

Column definitions were gathered from http://www.bom.gov.au/climate/dwo/IDCJDW0000.shtml