Finalizing Report

Schrick-Noah_Learning-Practice-6.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 139,
+   "execution_count": 190,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19,15 +19,12 @@
     "import pandas as pd\n",
     "from sklearn.linear_model import LogisticRegression, LogisticRegressionCV\n",
     "from sklearn.linear_model import LinearRegression, Lasso, Ridge, LassoCV, BayesianRidge\n",
-    "from dmba import backward_elimination, forward_selection, stepwise_selection\n",
-    "from dmba import regressionSummary, exhaustive_search\n",
+    "from dmba import stepwise_selection\n",
+    "from dmba import regressionSummary\n",
     "from sklearn.model_selection import train_test_split\n",
     "import statsmodels.api as sm\n",
-    "from mord import LogisticIT\n",
     "from pandas.plotting import scatter_matrix\n",
-    "import matplotlib.pylab as plt\n",
     "import seaborn as sns\n",
-    "from dmba import classificationSummary, gainsChart, liftChart\n",
     "from dmba.metric import AIC_score"
    ]
   },
@@ -53,7 +50,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 191,
    "metadata": {},
    "outputs": [
     {