35_downsample_size_loop_cust_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 - data generator randomization, NAICS+hierarchy\n",
    "Randomize training during fit (shuffled), loop downsampling training data.  Loop the downsample fraction.  (Fixed random injection at 10%"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e6fba8f-d564-466c-8e50-7773b095157f",
   "metadata": {},
   "source": [
    "NAICS+hierarchy groups, and data with no missing values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d47a7ec9-7d7b-47df-a902-b2f1e54f1135",
   "metadata": {},
   "source": [
    "*This script takes about 2 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\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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": 5,
   "id": "e9d62b12-8bbf-4f4f-90ca-9318dccadab4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.ticker as ticker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5dedd82d-1901-4327-8b7f-f00026a84f18",
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.callbacks import EarlyStopping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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": 8,
   "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": 9,
   "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": 10,
   "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": 11,
   "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": 12,
   "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": 13,
   "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": 14,
   "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": "b979396c-c822-4940-a292-6e07f1b54f58",
   "metadata": {},
   "source": [
    "##### Datasets for train, validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "43bca011-a59d-4496-9f03-87f4e350a253",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = sba_loans[['dset', 'LoanNr_ChkDgt'] + features_numeric + features_naics].set_index('LoanNr_ChkDgt').sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "aa162d01-ed73-4ae3-832e-4aeea09b70f4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training X: (446848, 14), 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": 17,
   "id": "b32b5fd3-6f6e-4aec-8e20-0e2b71a4814c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "val X: (95604, 14), 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": 18,
   "id": "01b8ff96-159b-4283-b5fb-c4b5dbd277d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.20230592953308507\n"
     ]
    }
   ],
   "source": [
    "base_thresh = y_train.mean()\n",
    "print(base_thresh)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3db4ea1c-77b2-4721-b106-1e66fc502139",
   "metadata": {},
   "source": [
    "## Create, fit model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53be11f2-9c6d-47d7-b5b6-55ca8ed1a4fe",
   "metadata": {},
   "source": [
    "## Loop for different fits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2a9a48fe-9d07-4fec-af0f-3f08e691cff4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def gen_fit_loop(rate=0.1, injection_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",
    "    y_train_ds = y_train.loc[train_samp]\n",
    "    \n",
    "    \n",
    "    generator = CatInjectGenerator(X_train_ds, y_train_ds,\n",
    "                               categorical_columns=features_naics,\n",
    "                               batch_size = setup.nn_batch_size,\n",
    "                               injection_rate = injection_rate,\n",
    "                               injection_value = 1)\n",
    "    callback = keras.callbacks.EarlyStopping(patience=3)\n",
    "    \n",
    "    this_history = this_model.fit(generator,\n",
    "                              batch_size=setup.nn_batch_size,\n",
    "                              epochs = setup.nn_epochs,\n",
    "                              validation_data=([X_val[features_numeric]] + [X_val[f] for f in features_naics], \n",
    "                                               y_val),\n",
    "                              shuffle=True,\n",
    "                             callbacks=[callback])\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[features_numeric]]+ [X[f] for f in features_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",
    "    this_metrics['train_size'] = len(train_samp)\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": 20,
   "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": 21,
   "id": "74f979e5-8aaa-4d0a-adea-70eac817d042",
   "metadata": {},
   "outputs": [],
   "source": [
    "history = pd.DataFrame()\n",
    "metrics = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9bdc1866-2381-4cde-a0ef-a1cd77133cba",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-05-25 23:43:25.289675: I metal_plugin/src/device/metal_device.cc:1154] Metal device set to: Apple M1\n",
      "2024-05-25 23:43:25.289791: I metal_plugin/src/device/metal_device.cc:296] systemMemory: 16.00 GB\n",
      "2024-05-25 23:43:25.289823: I metal_plugin/src/device/metal_device.cc:313] maxCacheSize: 5.33 GB\n",
      "2024-05-25 23:43:25.289984: 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 23:43:25.290029: 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 23:43:28.572673: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 23:43:45.465969: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 23:48:46.119011: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 23:51:17.352515: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
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      "2024-05-25 23:56:56.804595: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 23:58:27.792959: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-25 23:58:59.259390: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 00:05:03.395255: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 00:06:40.723079: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 00:07:40.894011: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 00:23:42.655781: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 00:25:34.785918: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 00:27:49.365944: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 00:46:21.711665: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 00:47:57.685476: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 00:51:31.236060: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 01:33:43.559530: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 01:34:33.277462: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 01:37:11.142841: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 01:52:25.013514: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 01:53:14.905167: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 01:56:00.613665: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 02:26:34.282203: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 02:27:24.367861: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 02:30:19.782632: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\n",
      "2024-05-26 02:54:07.075204: 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": 23,
   "id": "ad4783f2-8d0b-4850-a45a-3a4be8e63318",
   "metadata": {},
   "outputs": [],
   "source": [
    "history['epoch'] = history.groupby('rate').cumcount()\n",
    "history.to_csv(Path(setup.temp_path).joinpath('35_REPORT_loop_history.csv'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b1854de9-c6e9-41d4-813a-4c62d43b2bc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics.to_csv(Path(setup.temp_path).joinpath('35_REPORT_loop_metrics.csv'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d934b1b9-a617-4330-8f1e-f3b7c89b1e0f",
   "metadata": {},
   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dset</th>\n",
       "      <th>accuracy_score</th>\n",
       "      <th>f1_score</th>\n",
       "      <th>precision_score</th>\n",
       "      <th>recall_score</th>\n",
       "      <th>average_precision_score</th>\n",
       "      <th>roc_auc_score</th>\n",
       "      <th>dset_naics_holdout</th>\n",
       "      <th>rate</th>\n",
       "      <th>thresh</th>\n",
       "      <th>train_size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>test</td>\n",
       "      <td>0.583285</td>\n",
       "      <td>0.411834</td>\n",
       "      <td>0.288711</td>\n",
       "      <td>0.718053</td>\n",
       "      <td>0.323350</td>\n",
       "      <td>0.681036</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.16</td>\n",
       "      <td>4468</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>test</td>\n",
       "      <td>0.611698</td>\n",
       "      <td>0.426001</td>\n",
       "      <td>0.304435</td>\n",
       "      <td>0.709194</td>\n",
       "      <td>0.334376</td>\n",
       "      <td>0.695445</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.20</td>\n",
       "      <td>22342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>test</td>\n",
       "      <td>0.631393</td>\n",
       "      <td>0.434995</td>\n",
       "      <td>0.315869</td>\n",
       "      <td>0.698378</td>\n",
       "      <td>0.349724</td>\n",
       "      <td>0.706813</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.22</td>\n",
       "      <td>44684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>test</td>\n",
       "      <td>0.641659</td>\n",
       "      <td>0.442803</td>\n",
       "      <td>0.323652</td>\n",
       "      <td>0.700798</td>\n",
       "      <td>0.367540</td>\n",
       "      <td>0.716960</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.20</td>\n",
       "      <td>89369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>test</td>\n",
       "      <td>0.653034</td>\n",
       "      <td>0.443045</td>\n",
       "      <td>0.328738</td>\n",
       "      <td>0.679217</td>\n",
       "      <td>0.373389</td>\n",
       "      <td>0.721693</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.26</td>\n",
       "      <td>178739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>test</td>\n",
       "      <td>0.658016</td>\n",
       "      <td>0.445809</td>\n",
       "      <td>0.332322</td>\n",
       "      <td>0.677002</td>\n",
       "      <td>0.377454</td>\n",
       "      <td>0.724462</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.22</td>\n",
       "      <td>312793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>test</td>\n",
       "      <td>0.650554</td>\n",
       "      <td>0.447372</td>\n",
       "      <td>0.329586</td>\n",
       "      <td>0.696163</td>\n",
       "      <td>0.379171</td>\n",
       "      <td>0.726696</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.22</td>\n",
       "      <td>402163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>test</td>\n",
       "      <td>0.661082</td>\n",
       "      <td>0.448148</td>\n",
       "      <td>0.334853</td>\n",
       "      <td>0.677311</td>\n",
       "      <td>0.381015</td>\n",
       "      <td>0.727519</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.22</td>\n",
       "      <td>424505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>test</td>\n",
       "      <td>0.658664</td>\n",
       "      <td>0.447291</td>\n",
       "      <td>0.333300</td>\n",
       "      <td>0.679784</td>\n",
       "      <td>0.378234</td>\n",
       "      <td>0.725183</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.20</td>\n",
       "      <td>442379</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   dset  accuracy_score  f1_score  precision_score  recall_score  \\\n",
       "0  test        0.583285  0.411834         0.288711      0.718053   \n",
       "0  test        0.611698  0.426001         0.304435      0.709194   \n",
       "0  test        0.631393  0.434995         0.315869      0.698378   \n",
       "0  test        0.641659  0.442803         0.323652      0.700798   \n",
       "0  test        0.653034  0.443045         0.328738      0.679217   \n",
       "0  test        0.658016  0.445809         0.332322      0.677002   \n",
       "0  test        0.650554  0.447372         0.329586      0.696163   \n",
       "0  test        0.661082  0.448148         0.334853      0.677311   \n",
       "0  test        0.658664  0.447291         0.333300      0.679784   \n",
       "\n",
       "   average_precision_score  roc_auc_score  dset_naics_holdout  rate  thresh  \\\n",
       "0                 0.323350       0.681036                 0.0  0.01    0.16   \n",
       "0                 0.334376       0.695445                 0.0  0.05    0.20   \n",
       "0                 0.349724       0.706813                 0.0  0.10    0.22   \n",
       "0                 0.367540       0.716960                 0.0  0.20    0.20   \n",
       "0                 0.373389       0.721693                 0.0  0.40    0.26   \n",
       "0                 0.377454       0.724462                 0.0  0.70    0.22   \n",
       "0                 0.379171       0.726696                 0.0  0.90    0.22   \n",
       "0                 0.381015       0.727519                 0.0  0.95    0.22   \n",
       "0                 0.378234       0.725183                 0.0  0.99    0.20   \n",
       "\n",
       "   train_size  \n",
       "0        4468  \n",
       "0       22342  \n",
       "0       44684  \n",
       "0       89369  \n",
       "0      178739  \n",
       "0      312793  \n",
       "0      402163  \n",
       "0      424505  \n",
       "0      442379  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics[metrics['dset_naics_holdout'] == 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "73e89efd-75a9-4b27-81a8-13e12d5482be",
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.26</td>\n",
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       "      <td>0.653059</td>\n",
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       "      <td>0.330498</td>\n",
       "      <td>0.722353</td>\n",
       "      <td>0.385993</td>\n",
       "      <td>0.739275</td>\n",
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       "      <td>0.331353</td>\n",
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       "      <td>0.386644</td>\n",
       "      <td>0.739613</td>\n",
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       "      <td>0.22</td>\n",
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       "      <td>0.453860</td>\n",
       "      <td>0.341248</td>\n",
       "      <td>0.677402</td>\n",
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       "      <td>test</td>\n",
       "      <td>0.656868</td>\n",
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      ],
      "text/plain": [
       "   dset  accuracy_score  f1_score  precision_score  recall_score  \\\n",
       "1  test        0.592458  0.432083         0.299104      0.777952   \n",
       "1  test        0.614757  0.438580         0.309042      0.755084   \n",
       "1  test        0.651441  0.445717         0.326247      0.703238   \n",
       "1  test        0.653146  0.452035         0.329871      0.717902   \n",
       "1  test        0.648797  0.446898         0.325655      0.711966   \n",
       "1  test        0.653059  0.453504         0.330498      0.722353   \n",
       "1  test        0.655581  0.452935         0.331353      0.715458   \n",
       "1  test        0.675114  0.453860         0.341248      0.677402   \n",
       "1  test        0.656868  0.454980         0.332848      0.718687   \n",
       "\n",
       "   average_precision_score  roc_auc_score  dset_naics_holdout  rate  thresh  \\\n",
       "1                 0.316470       0.704282                 1.0  0.01    0.16   \n",
       "1                 0.339283       0.715528                 1.0  0.05    0.20   \n",
       "1                 0.354953       0.724119                 1.0  0.10    0.22   \n",
       "1                 0.375107       0.733081                 1.0  0.20    0.20   \n",
       "1                 0.379455       0.733604                 1.0  0.40    0.26   \n",
       "1                 0.385993       0.739275                 1.0  0.70    0.22   \n",
       "1                 0.386644       0.739613                 1.0  0.90    0.22   \n",
       "1                 0.384249       0.738992                 1.0  0.95    0.22   \n",
       "1                 0.384988       0.740343                 1.0  0.99    0.20   \n",
       "\n",
       "   train_size  \n",
       "1        4468  \n",
       "1       22342  \n",
       "1       44684  \n",
       "1       89369  \n",
       "1      178739  \n",
       "1      312793  \n",
       "1      402163  \n",
       "1      424505  \n",
       "1      442379  "
      ]
     },
     "execution_count": 26,
     "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": 27,
   "id": "ae6c4e12-c72e-4f71-aaca-62f0704dca6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#metrics = pd.read_csv(Path(setup.temp_path).joinpath('35_REPORT_loop_metrics.csv'))\n",
    "#history = pd.read_csv(Path(setup.temp_path).joinpath('35_REPORT_loop_history.csv'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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": 28,
     "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": 29,
   "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('35_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": 30,
   "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": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "importlib.reload(sbnn_plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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('35_PLOT_hostory_val_auc.png'),\n",
    "            bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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('35_PLOT_hostory_val_loss.png'),\n",
    "            bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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('35_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
}