testfigure.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.datasets import load_iris"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f47a49c7ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from triage.component.postmodeling.contrast.model_evaluator import ModelEvaluator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "X, y = load_iris(return_X_y=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_label =y[y<2]\n",
    "X_label = X[y<2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/avishek/miniconda3/envs/py36/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "mdl = LogisticRegression().fit(X_label,y_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_score = mdl.predict_proba(X_label)[:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_predictions = pd.DataFrame()\n",
    "df_predictions['label_value'] = y_label\n",
    "df_predictions['score'] = y_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_model = ModelEvaluator(model_group_id=1, model_id=2, engine=None)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_model.predictions = df_predictions "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f479b867be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_model.plot_reliability_curve()"
   ]
  },
  {
   "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": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}