31_downsample_size_loop_raw_hier.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8816b366-5be4-4748-b769-4dc6f7d1735f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Modify the file 00_setup.py to define input/output file paths on your system\n",
    "# The information in 00_setup.py will be used across notebooks\n",
    "from importlib.machinery import SourceFileLoader\n",
    "setup = SourceFileLoader(\"setup\", \"./00_setup.py\").load_module()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a945de0c-f042-46b2-9d06-ab064af6c05b",
   "metadata": {},
   "source": [
    "## Loop downsample size - raw NAICS hierarchy\n",
    "Do the no-randomization models, downsampling training data.  Loop the downsample fraction. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e6fba8f-d564-466c-8e50-7773b095157f",
   "metadata": {},
   "source": [
    "NAICS+hierarchy, and data with no missing values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d47a7ec9-7d7b-47df-a902-b2f1e54f1135",
   "metadata": {},
   "source": [
    "*This script takes about 4 hours on my MacBook Air*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fb42f9b4-99a8-4753-aacf-8722469be4c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bf51170a-4487-4d10-b63d-c88f41b529f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "import importlib, pickle\n",
    "from sklearn import model_selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "edd1164e-3ceb-4e3a-ad25-79bb9cf19a2f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "09dd973b-60a0-434b-9193-8c5fcec27dd5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "import re\n",
    "\n",
    "import keras\n",
    "from tensorflow.keras import layers, optimizers, losses, metrics, Model\n",
    "from sklearn import preprocessing, feature_extraction, model_selection\n",
    "from IPython.display import display, HTML\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e9d62b12-8bbf-4f4f-90ca-9318dccadab4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.ticker as ticker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5dedd82d-1901-4327-8b7f-f00026a84f18",
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.callbacks import EarlyStopping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9f1e4f2e-0e45-4e28-8e9c-212e0bb51199",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sba_nn.sba_nn import sbnn_metrics, sbnn_model, sbnn_plot\n",
    "from sba_nn.sba_nn.sbnn_model import CatInjectGenerator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2a50c5c6-be2c-43a5-9795-d9eabb8a5f5c",
   "metadata": {},
   "outputs": [],
   "source": [
    "sbnn_plot.plot_defaults()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cbc00d2-bc83-42d9-83eb-65fcf306dccd",
   "metadata": {},
   "source": [
    "## Input Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e014cd31-0f8d-42e3-82f9-b529eec8a3cc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "sba_loans = pd.read_parquet(Path(setup.temp_path).joinpath('01_DATA_transformed_nomiss.parquet'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8e65cb7c-792c-46ff-a530-0d5c64240d60",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(Path(setup.temp_path).joinpath('01_DATA_features.pkl'), 'rb') as fin:\n",
    "    imputer_features = pickle.load(fin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6f0ce28e-a80c-415b-b068-5c4d49370da8",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(Path(setup.temp_path).joinpath('01_DATA_naics_max_encodings.pkl'), 'rb') as fin:\n",
    "    naics_max_levels= pickle.load(fin)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d4116da-d689-478a-9c5d-a330f231e615",
   "metadata": {},
   "source": [
    "##### Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f98c6e41-38d0-4d5f-b821-e3837b8c2068",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['NoEmp', 'CreateJob', 'LowDoc', 'DisbursementGross', 'new_business', 'urban_flag', 'franchise_flag', 'missingindicator_LowDoc', 'missingindicator_new_business', 'missingindicator_urban_flag']\n"
     ]
    }
   ],
   "source": [
    "# Numeric features\n",
    "features_numeric = [f for f in imputer_features if 'NAICS' not in f]\n",
    "features_numeric_len = len(features_numeric)\n",
    "print(features_numeric)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ba637a7a-6d62-4e7d-b869-b72be58fd37a",
   "metadata": {},
   "outputs": [],
   "source": [
    "###### NAICS feature\n",
    "features_naics = ['NAICS', 'NAICS_4', 'NAICS_3', 'NAICS_sector']\n",
    "features_naics_max_levels  = [naics_max_levels[n] for n in features_naics]\n",
    "features_naics_emb_dim = [setup.nn_naics_embed_size_dict[n] for n in features_naics]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "867031ee-8b6e-424d-b497-8e19409ba1d9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1170, 345, 107, 21]\n",
      "[8, 4, 4, 2]\n"
     ]
    }
   ],
   "source": [
    "print(features_naics_max_levels)\n",
    "print(features_naics_emb_dim)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e2b5f20-0cd1-405a-9c40-8bf45aa89159",
   "metadata": {},
   "source": [
    "##### Datasets for train, validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "0df27034-65fb-4d46-a013-eab2bcc96616",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = sba_loans[['dset', 'LoanNr_ChkDgt'] + features_numeric].set_index('LoanNr_ChkDgt').sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c148e947-444d-4f2f-97c0-ae780485895c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training X: (446848, 10), y:(446848,)\n"
     ]
    }
   ],
   "source": [
    "X_train = X[X['dset'] == 'train'].drop(columns='dset')\n",
    "y_train = sba_loans[sba_loans['dset'] == 'train'].set_index('LoanNr_ChkDgt').sort_index()['target']\n",
    "print(f'training X: {X_train.shape}, y:{y_train.shape}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2668f340-3d2f-4c46-8908-57c9cbfbf7c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "val X: (95604, 10), y:(95604,)\n"
     ]
    }
   ],
   "source": [
    "X_val = X[X['dset'] == 'val'].drop(columns='dset')\n",
    "y_val = sba_loans[sba_loans['dset'] == 'val'].set_index('LoanNr_ChkDgt').sort_index()['target']\n",
    "print(f'val X: {X_val.shape}, y:{y_val.shape}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "069063dd-d090-494d-8ebc-a048f6272128",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.20230592953308507\n"
     ]
    }
   ],
   "source": [
    "base_thresh = y_train.mean()\n",
    "print(base_thresh)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "3ce4d67e-654a-4117-8381-3e97993cc653",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_naics = [sba_loans[['dset', 'LoanNr_ChkDgt', n]].set_index('LoanNr_ChkDgt').sort_index() \\\n",
    "           for n in features_naics]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e0347be3-bfa0-4097-b7d5-e7d0e5a7e133",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_naics_train = [Xn[Xn['dset'] == 'train'].drop(columns='dset') for Xn in X_naics]\n",
    "X_naics_val =  [Xn[Xn['dset'] == 'val'].drop(columns='dset') for Xn in X_naics]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53be11f2-9c6d-47d7-b5b6-55ca8ed1a4fe",
   "metadata": {},
   "source": [
    "## Loop for different fits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2a9a48fe-9d07-4fec-af0f-3f08e691cff4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def gen_fit_loop(rate = 0.1):\n",
    "    this_model = sbnn_model.create_emb_model(features_numeric_len,\n",
    "                                         features_naics_max_levels,\n",
    "                                         features_naics_emb_dim,\n",
    "                                         naics_embedding_names = features_naics,\n",
    "                                         hidden_size = setup.nn_layer_sizes,\n",
    "                                         activation='tanh',\n",
    "                                         lr=setup.nn_learning_rate,\n",
    "                                         opt_func = setup.nn_optimizer,\n",
    "                                         dropout = setup.nn_dropout)\n",
    "    \n",
    "    # Downsample\n",
    "    train_samp, _ = train_test_split(X_train.index,\n",
    "                                train_size=rate,\n",
    "                                random_state=343)\n",
    "    X_train_ds = X_train.loc[train_samp, :]\n",
    "    X_naics_train_ds = [xn.loc[train_samp, :] for xn in X_naics_train]\n",
    "    y_train_ds = y_train.loc[train_samp]\n",
    "    \n",
    "    callback = keras.callbacks.EarlyStopping(patience=3)\n",
    "    \n",
    "    # Fit\n",
    "    this_history = this_model.fit([X_train_ds] + X_naics_train_ds, y_train_ds,\n",
    "                              validation_data=([X_val] + X_naics_val, y_val),\n",
    "                              batch_size=setup.nn_batch_size,\n",
    "                              epochs=setup.nn_epochs,\n",
    "                              callbacks=[callback],\n",
    "                                 shuffle=True)\n",
    "    \n",
    "    this_history_df = sbnn_model.process_history(this_history)\n",
    "    this_history_df['rate'] = rate\n",
    "    \n",
    "    # Predictions then metrics\n",
    "    this_predict = this_model.predict([X.drop(columns='dset')] +\n",
    "                                     [Xn.drop(columns='dset') for Xn in X_naics])\n",
    "    this_predict_df = pd.DataFrame(this_predict, index=X.index) \\\n",
    "        .set_axis(['predict_prob'], axis=1) \\\n",
    "        .reset_index() \\\n",
    "        .merge(sba_loans[['target', 'LoanNr_ChkDgt', 'dset', 'dset_naics_holdout', 'NAICS']], \n",
    "               on='LoanNr_ChkDgt')\n",
    "    \n",
    "    # Threshold tune\n",
    "    this_pred_train = this_predict_df[this_predict_df['dset'] == 'train']\n",
    "    thresh_tune_data = sbnn_metrics.get_f1_frame(this_pred_train['target'], \n",
    "                                        this_pred_train['predict_prob'])\n",
    "    thresh_tune_data.sort_values('f1', ascending=False, inplace=True)\n",
    "    best_thresh = thresh_tune_data['thresh'].iloc[0]\n",
    "    this_predict_df['predict_bin'] = sbnn_metrics.get_binary_predictions(this_predict_df['predict_prob'], \n",
    "                                                                            best_thresh)\n",
    "    \n",
    "    this_metrics_dset = this_predict_df.groupby('dset') \\\n",
    "        .apply(lambda x: sbnn_metrics.dset_metrics(x.target, x.predict_bin, x.predict_prob)) \\\n",
    "        .reset_index()\n",
    "    this_metrics_test = this_predict_df[this_predict_df['dset'] == 'test'] \\\n",
    "        .groupby(['dset', 'dset_naics_holdout']) \\\n",
    "        .apply(lambda x: sbnn_metrics.dset_metrics(x.target, x.predict_bin, x.predict_prob)) \\\n",
    "        .reset_index()\n",
    "    this_metrics = pd.concat([this_metrics_dset, this_metrics_test])\n",
    "    this_metrics['rate'] = rate\n",
    "    this_metrics['thresh'] = best_thresh\n",
    "    \n",
    "    return this_history_df, this_metrics\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "375ed31d-be98-458c-97ba-dc86cddacc18",
   "metadata": {},
   "source": [
    "## Run Loop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f2773b95-7041-41cc-ac49-4a5310138fe9",
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_rate_vals = [0.01, 0.05, 0.1, 0.2, 0.4, 0.7, 0.9, 0.95, 0.99]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "74f979e5-8aaa-4d0a-adea-70eac817d042",
   "metadata": {},
   "outputs": [],
   "source": [
    "history = pd.DataFrame()\n",
    "metrics = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "9bdc1866-2381-4cde-a0ef-a1cd77133cba",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-05-25 21:02:30.931111: I metal_plugin/src/device/metal_device.cc:1154] Metal device set to: Apple M1\n",
      "2024-05-25 21:02:30.931139: I metal_plugin/src/device/metal_device.cc:296] systemMemory: 16.00 GB\n",
      "2024-05-25 21:02:30.931147: I metal_plugin/src/device/metal_device.cc:313] maxCacheSize: 5.33 GB\n",
      "2024-05-25 21:02:30.931190: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:303] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.\n",
      "2024-05-25 21:02:30.931207: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:269] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)\n",
      "2024-05-25 21:02:32.046318: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:02:36.307196: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:06:55.694561: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:08:51.113766: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:09:09.648817: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:12:51.385112: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:14:27.546394: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:15:02.280157: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:22:05.919118: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:23:42.239112: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:24:50.169328: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:42:02.113131: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:43:38.440083: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 21:45:51.735572: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 22:08:42.964188: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 22:10:22.982435: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 22:14:23.884142: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 22:46:06.782182: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 22:47:17.408579: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 22:51:28.229367: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 23:25:45.724180: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 23:27:28.836997: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 23:32:50.142664: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 00:55:51.468976: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 00:56:58.615278: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 01:00:44.289601: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 01:29:39.569899: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n"
     ]
    }
   ],
   "source": [
    "%%capture\n",
    "for r in sample_rate_vals:\n",
    "    this_hist, this_met = gen_fit_loop(r)\n",
    "    history = pd.concat([history, this_hist])\n",
    "    metrics = pd.concat([metrics, this_met])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ad4783f2-8d0b-4850-a45a-3a4be8e63318",
   "metadata": {},
   "outputs": [],
   "source": [
    "history['epoch'] = history.groupby('rate').cumcount()\n",
    "history.to_csv(Path(setup.temp_path).joinpath('31_REPORT_loop_history.csv'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b1854de9-c6e9-41d4-813a-4c62d43b2bc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics.to_csv(Path(setup.temp_path).joinpath('31_REPORT_loop_metrics.csv'))"
   ]
  },
  {
   "cell_type": "code",
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   "id": "d934b1b9-a617-4330-8f1e-f3b7c89b1e0f",
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       "      <td>0.376521</td>\n",
       "      <td>0.723940</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.20</td>\n",
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       "      <td>0.328671</td>\n",
       "      <td>0.705588</td>\n",
       "      <td>0.380975</td>\n",
       "      <td>0.727268</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.99</td>\n",
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      "text/plain": [
       "   dset  accuracy_score  f1_score  precision_score  recall_score  \\\n",
       "0  test        0.584164  0.399250         0.282565      0.680093   \n",
       "0  test        0.587555  0.423801         0.295886      0.746536   \n",
       "0  test        0.623942  0.433461         0.312332      0.708061   \n",
       "0  test        0.642057  0.440672         0.322831      0.693999   \n",
       "0  test        0.657880  0.443275         0.331112      0.670358   \n",
       "0  test        0.651820  0.446194         0.329620      0.690343   \n",
       "0  test        0.645950  0.446031         0.326956      0.701519   \n",
       "0  test        0.669213  0.448581         0.339163      0.662220   \n",
       "0  test        0.647362  0.448449         0.328671      0.705588   \n",
       "\n",
       "   average_precision_score  roc_auc_score  dset_naics_holdout  rate  thresh  \n",
       "0                 0.308767       0.663813                 0.0  0.01    0.16  \n",
       "0                 0.333650       0.694496                 0.0  0.05    0.16  \n",
       "0                 0.347295       0.704246                 0.0  0.10    0.18  \n",
       "0                 0.366607       0.715652                 0.0  0.20    0.18  \n",
       "0                 0.371518       0.721016                 0.0  0.40    0.24  \n",
       "0                 0.376521       0.723940                 0.0  0.70    0.20  \n",
       "0                 0.379831       0.726073                 0.0  0.90    0.22  \n",
       "0                 0.380598       0.727831                 0.0  0.95    0.22  \n",
       "0                 0.380975       0.727268                 0.0  0.99    0.20  "
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     "metadata": {},
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    }
   ],
   "source": [
    "metrics[metrics['dset_naics_holdout'] == 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "73e89efd-75a9-4b27-81a8-13e12d5482be",
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   "outputs": [
    {
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       "      <td>0.288839</td>\n",
       "      <td>0.850484</td>\n",
       "      <td>0.371859</td>\n",
       "      <td>0.733427</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.20</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>test</td>\n",
       "      <td>0.554852</td>\n",
       "      <td>0.433053</td>\n",
       "      <td>0.290176</td>\n",
       "      <td>0.853103</td>\n",
       "      <td>0.379937</td>\n",
       "      <td>0.736512</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.22</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>test</td>\n",
       "      <td>0.523578</td>\n",
       "      <td>0.423538</td>\n",
       "      <td>0.279058</td>\n",
       "      <td>0.878240</td>\n",
       "      <td>0.373376</td>\n",
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       "      <td>0.95</td>\n",
       "      <td>0.22</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>test</td>\n",
       "      <td>0.554869</td>\n",
       "      <td>0.432811</td>\n",
       "      <td>0.290060</td>\n",
       "      <td>0.852230</td>\n",
       "      <td>0.374097</td>\n",
       "      <td>0.736298</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.20</td>\n",
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      ],
      "text/plain": [
       "   dset  accuracy_score  f1_score  precision_score  recall_score  \\\n",
       "1  test        0.462316  0.401858         0.258161      0.906345   \n",
       "1  test        0.462281  0.404974         0.259772      0.918216   \n",
       "1  test        0.565915  0.432586         0.292483      0.830322   \n",
       "1  test        0.523404  0.423449         0.278981      0.878240   \n",
       "1  test        0.571046  0.436642         0.295718      0.834163   \n",
       "1  test        0.552904  0.431227         0.288839      0.850484   \n",
       "1  test        0.554852  0.433053         0.290176      0.853103   \n",
       "1  test        0.523578  0.423538         0.279058      0.878240   \n",
       "1  test        0.554869  0.432811         0.290060      0.852230   \n",
       "\n",
       "   average_precision_score  roc_auc_score  dset_naics_holdout  rate  thresh  \n",
       "1                 0.317949       0.696121                 1.0  0.01    0.16  \n",
       "1                 0.334652       0.711379                 1.0  0.05    0.16  \n",
       "1                 0.351483       0.721835                 1.0  0.10    0.18  \n",
       "1                 0.360074       0.730374                 1.0  0.20    0.18  \n",
       "1                 0.364981       0.731568                 1.0  0.40    0.24  \n",
       "1                 0.371859       0.733427                 1.0  0.70    0.20  \n",
       "1                 0.379937       0.736512                 1.0  0.90    0.22  \n",
       "1                 0.373376       0.732151                 1.0  0.95    0.22  \n",
       "1                 0.374097       0.736298                 1.0  0.99    0.20  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics[metrics['dset_naics_holdout'] == 1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0dae1f5-a6e2-46c3-bba7-f0966f93d3ed",
   "metadata": {},
   "source": [
    "## Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ae6c4e12-c72e-4f71-aaca-62f0704dca6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#metrics = pd.read_csv(Path(setup.temp_path).joinpath('31_REPORT_loop_metrics.csv'))\n",
    "#history = pd.read_csv(Path(setup.temp_path).joinpath('31_REPORT_loop_history.csv'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b14d8c25-2623-40be-a84c-43c752f60fa7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'sba_nn.sba_nn.sbnn_plot' from '/Users/valeriecarey/Documents/projects/2024_05_blog_nn_rand/code/sba_nn/sba_nn/sbnn_plot.py'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "importlib.reload(sbnn_plot)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7fba165-3d44-4a97-8227-03057298768b",
   "metadata": {},
   "source": [
    "##### Metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "5126ef4e-45a3-4a1c-9dba-37c59b8f75ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = sbnn_plot.plot_metric_dependence(metrics, xformatter = ticker.PercentFormatter(1),\n",
    "                                      ylabel='PR-AUC',\n",
    "                            xlabel='downsample rate')\n",
    "fig.savefig(Path(setup.temp_path).joinpath('31_PLOT_average_precision.png'),\n",
    "            bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26e38578-60a3-4986-bd7f-fd76b992f135",
   "metadata": {},
   "source": [
    "##### History"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ffc7e367-f428-4f76-a517-4faa77cf7095",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'sba_nn.sba_nn.sbnn_plot' from '/Users/valeriecarey/Documents/projects/2024_05_blog_nn_rand/code/sba_nn/sba_nn/sbnn_plot.py'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "importlib.reload(sbnn_plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "2342a31f-4891-4834-851a-b90b8b729c3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = sbnn_plot.plot_history_group(history,\n",
    "                                  col_format_func = lambda x:f'{float(x):.1%}',\n",
    "                                  ylabel = 'PR-AUC (validation)',\n",
    "                                  leg_title='down rate')\n",
    "fig.savefig(Path(setup.temp_path).joinpath('31_PLOT_hostory_val_auc.png'),\n",
    "            bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "9e92ea2f-378d-47a1-b067-2ec715935c9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = sbnn_plot.plot_history_group(history,'val_loss',\n",
    "                                  col_format_func = lambda x:f'{float(x):.1%}',\n",
    "                                  ylabel = 'Loss (validation)',\n",
    "                                  leg_title='down rate')\n",
    "fig.savefig(Path(setup.temp_path).joinpath('31_PLOT_hostory_val_loss.png'),\n",
    "            bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "0c6acda4-3326-4ece-9ae9-8fc784e9475f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = sbnn_plot.plot_epoch_agg(history,\n",
    "                               xformatter = ticker.PercentFormatter(1),\n",
    "                               ylabel='# Epochs',\n",
    "                               xlabel='downsample rate')\n",
    "fig.savefig(Path(setup.temp_path).joinpath('31_PLOT_hostory_epochs.png'),\n",
    "            bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b5334471-c99c-44c5-9e2b-4c1b6e602b4a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "tf_p39",
   "language": "python",
   "name": "tf_p39"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}