{ "cells": [ { "cell_type": "code", "execution_count": 19, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "from sklearn.datasets import load_breast_cancer\n", "from sklearn.neighbors import KNeighborsClassifier\n", "from sklearn.model_selection import train_test_split\n", "\n", "import matplotlib.pyplot as plt\n", "import mglearn\n", "\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "cancer = load_breast_cancer()" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "# Knowledge Gathering \n", "\n", "#print(cancer.DESCR)\n", "#cancer.data\n", "#cancer.data.shape\n", "#print(cancer.feature_names)\n", "#print(cancer.target_names)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true, "deletable": true, "editable": true }, "source": [ "