819 lines
20 KiB
Plaintext
819 lines
20 KiB
Plaintext
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{
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"cells": [
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from sklearn.preprocessing import MinMaxScaler"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"data = np.random.randint(0,100,(10,2))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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"text/plain": [
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"array([[53, 52],\n",
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" [82, 96],\n",
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" [60, 84],\n",
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" [15, 90],\n",
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" [78, 31],\n",
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" [ 5, 12],\n",
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" [80, 39],\n",
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" [31, 46],\n",
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" [22, 29]])"
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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"source": [
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"data"
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"scaler_model = MinMaxScaler()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"sklearn.preprocessing._data.MinMaxScaler"
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"execution_count": 7,
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"output_type": "execute_result"
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}
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"source": [
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"type(scaler_model)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"MinMaxScaler(copy=True, feature_range=(0, 1))"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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"source": [
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"scaler_model.fit(data)"
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"text/plain": [
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"array([[0.62337662, 0.47619048],\n",
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" [1. , 1. ],\n",
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" [0.71428571, 0.85714286],\n",
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" [0.12987013, 0.92857143],\n",
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" [0.94805195, 0.22619048],\n",
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" [0. , 0. ],\n",
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" [0.33766234, 0.4047619 ],\n",
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" [0.22077922, 0.20238095]])"
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"execution_count": 9,
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"output_type": "execute_result"
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}
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],
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"source": [
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"scaler_model.transform(data)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"array([[0.62337662, 0.47619048],\n",
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" [0. , 0. ],\n",
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" [0.22077922, 0.20238095]])"
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"scaler_model.fit_transform(data)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/Users/eddie/.pyenv/versions/3.7.3/envs/tensorflow-1.14/lib/python3.7/site-packages/pandas/compat/__init__.py:117: UserWarning: Could not import the lzma module. Your installed Python is incomplete. Attempting to use lzma compression will result in a RuntimeError.\n",
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" warnings.warn(msg)\n"
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]
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}
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],
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"source": [
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"import pandas as pd"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [],
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"source": [
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"mydata = np.random.randint(0,101,(50,4))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"array([[ 97, 70, 23, 81],\n",
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"output_type": "execute_result"
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}
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],
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"source": [
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"mydata"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pd.DataFrame(data=mydata, columns = ['f1','f2','f3','label'])"
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]
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},
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"cell_type": "code",
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"execution_count": 17,
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"metadata": {},
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"outputs": [
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>f1</th>\n",
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" <th>f2</th>\n",
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" <th>f3</th>\n",
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" <th>label</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>97</td>\n",
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" <td>70</td>\n",
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" <td>23</td>\n",
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" <td>81</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>60</td>\n",
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" <td>40</td>\n",
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" <td>73</td>\n",
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" <td>7</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>60</td>\n",
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" <td>88</td>\n",
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" <td>87</td>\n",
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" <td>67</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>42</td>\n",
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" <td>25</td>\n",
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" <td>81</td>\n",
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" <td>100</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>45</td>\n",
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" <td>30</td>\n",
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" <td>69</td>\n",
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" <td>72</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>5</th>\n",
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" <td>16</td>\n",
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" <td>100</td>\n",
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" <td>70</td>\n",
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" <td>14</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>6</th>\n",
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" <td>25</td>\n",
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" <td>76</td>\n",
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" <td>32</td>\n",
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" <td>70</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>7</th>\n",
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" <td>2</td>\n",
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" <td>29</td>\n",
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" <td>46</td>\n",
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" <td>65</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>8</th>\n",
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" <td>71</td>\n",
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" <td>33</td>\n",
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" <td>11</td>\n",
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" <td>79</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>9</th>\n",
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" <td>98</td>\n",
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" <td>16</td>\n",
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" <td>76</td>\n",
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" <td>9</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>10</th>\n",
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" <td>0</td>\n",
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" <td>78</td>\n",
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" <td>61</td>\n",
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" <td>34</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>11</th>\n",
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" <td>78</td>\n",
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" <td>43</td>\n",
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" <td>45</td>\n",
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" <td>87</td>\n",
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|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>12</th>\n",
|
||
|
|
" <td>95</td>\n",
|
||
|
|
" <td>78</td>\n",
|
||
|
|
" <td>6</td>\n",
|
||
|
|
" <td>34</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>13</th>\n",
|
||
|
|
" <td>14</td>\n",
|
||
|
|
" <td>44</td>\n",
|
||
|
|
" <td>95</td>\n",
|
||
|
|
" <td>27</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>14</th>\n",
|
||
|
|
" <td>32</td>\n",
|
||
|
|
" <td>31</td>\n",
|
||
|
|
" <td>90</td>\n",
|
||
|
|
" <td>58</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>15</th>\n",
|
||
|
|
" <td>72</td>\n",
|
||
|
|
" <td>15</td>\n",
|
||
|
|
" <td>16</td>\n",
|
||
|
|
" <td>59</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>16</th>\n",
|
||
|
|
" <td>5</td>\n",
|
||
|
|
" <td>72</td>\n",
|
||
|
|
" <td>31</td>\n",
|
||
|
|
" <td>36</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>17</th>\n",
|
||
|
|
" <td>72</td>\n",
|
||
|
|
" <td>30</td>\n",
|
||
|
|
" <td>94</td>\n",
|
||
|
|
" <td>55</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>18</th>\n",
|
||
|
|
" <td>55</td>\n",
|
||
|
|
" <td>19</td>\n",
|
||
|
|
" <td>91</td>\n",
|
||
|
|
" <td>74</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>19</th>\n",
|
||
|
|
" <td>9</td>\n",
|
||
|
|
" <td>20</td>\n",
|
||
|
|
" <td>10</td>\n",
|
||
|
|
" <td>34</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>20</th>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>6</td>\n",
|
||
|
|
" <td>25</td>\n",
|
||
|
|
" <td>49</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>21</th>\n",
|
||
|
|
" <td>63</td>\n",
|
||
|
|
" <td>61</td>\n",
|
||
|
|
" <td>86</td>\n",
|
||
|
|
" <td>55</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>22</th>\n",
|
||
|
|
" <td>25</td>\n",
|
||
|
|
" <td>21</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>85</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>23</th>\n",
|
||
|
|
" <td>80</td>\n",
|
||
|
|
" <td>66</td>\n",
|
||
|
|
" <td>73</td>\n",
|
||
|
|
" <td>51</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>24</th>\n",
|
||
|
|
" <td>96</td>\n",
|
||
|
|
" <td>46</td>\n",
|
||
|
|
" <td>35</td>\n",
|
||
|
|
" <td>58</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>25</th>\n",
|
||
|
|
" <td>7</td>\n",
|
||
|
|
" <td>4</td>\n",
|
||
|
|
" <td>89</td>\n",
|
||
|
|
" <td>25</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>26</th>\n",
|
||
|
|
" <td>92</td>\n",
|
||
|
|
" <td>11</td>\n",
|
||
|
|
" <td>77</td>\n",
|
||
|
|
" <td>59</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>27</th>\n",
|
||
|
|
" <td>38</td>\n",
|
||
|
|
" <td>94</td>\n",
|
||
|
|
" <td>19</td>\n",
|
||
|
|
" <td>46</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>28</th>\n",
|
||
|
|
" <td>34</td>\n",
|
||
|
|
" <td>24</td>\n",
|
||
|
|
" <td>94</td>\n",
|
||
|
|
" <td>70</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>29</th>\n",
|
||
|
|
" <td>100</td>\n",
|
||
|
|
" <td>91</td>\n",
|
||
|
|
" <td>46</td>\n",
|
||
|
|
" <td>76</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>30</th>\n",
|
||
|
|
" <td>43</td>\n",
|
||
|
|
" <td>10</td>\n",
|
||
|
|
" <td>35</td>\n",
|
||
|
|
" <td>78</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>31</th>\n",
|
||
|
|
" <td>15</td>\n",
|
||
|
|
" <td>24</td>\n",
|
||
|
|
" <td>57</td>\n",
|
||
|
|
" <td>6</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>32</th>\n",
|
||
|
|
" <td>51</td>\n",
|
||
|
|
" <td>47</td>\n",
|
||
|
|
" <td>47</td>\n",
|
||
|
|
" <td>55</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>33</th>\n",
|
||
|
|
" <td>83</td>\n",
|
||
|
|
" <td>5</td>\n",
|
||
|
|
" <td>84</td>\n",
|
||
|
|
" <td>40</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>34</th>\n",
|
||
|
|
" <td>100</td>\n",
|
||
|
|
" <td>22</td>\n",
|
||
|
|
" <td>26</td>\n",
|
||
|
|
" <td>72</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>35</th>\n",
|
||
|
|
" <td>60</td>\n",
|
||
|
|
" <td>83</td>\n",
|
||
|
|
" <td>80</td>\n",
|
||
|
|
" <td>92</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>36</th>\n",
|
||
|
|
" <td>28</td>\n",
|
||
|
|
" <td>39</td>\n",
|
||
|
|
" <td>82</td>\n",
|
||
|
|
" <td>17</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>37</th>\n",
|
||
|
|
" <td>56</td>\n",
|
||
|
|
" <td>20</td>\n",
|
||
|
|
" <td>94</td>\n",
|
||
|
|
" <td>85</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>38</th>\n",
|
||
|
|
" <td>72</td>\n",
|
||
|
|
" <td>56</td>\n",
|
||
|
|
" <td>63</td>\n",
|
||
|
|
" <td>54</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>39</th>\n",
|
||
|
|
" <td>15</td>\n",
|
||
|
|
" <td>60</td>\n",
|
||
|
|
" <td>30</td>\n",
|
||
|
|
" <td>72</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>40</th>\n",
|
||
|
|
" <td>41</td>\n",
|
||
|
|
" <td>21</td>\n",
|
||
|
|
" <td>86</td>\n",
|
||
|
|
" <td>54</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>41</th>\n",
|
||
|
|
" <td>85</td>\n",
|
||
|
|
" <td>7</td>\n",
|
||
|
|
" <td>50</td>\n",
|
||
|
|
" <td>87</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>42</th>\n",
|
||
|
|
" <td>48</td>\n",
|
||
|
|
" <td>13</td>\n",
|
||
|
|
" <td>69</td>\n",
|
||
|
|
" <td>93</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>43</th>\n",
|
||
|
|
" <td>75</td>\n",
|
||
|
|
" <td>20</td>\n",
|
||
|
|
" <td>98</td>\n",
|
||
|
|
" <td>96</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>44</th>\n",
|
||
|
|
" <td>41</td>\n",
|
||
|
|
" <td>18</td>\n",
|
||
|
|
" <td>14</td>\n",
|
||
|
|
" <td>31</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>45</th>\n",
|
||
|
|
" <td>84</td>\n",
|
||
|
|
" <td>13</td>\n",
|
||
|
|
" <td>62</td>\n",
|
||
|
|
" <td>6</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>46</th>\n",
|
||
|
|
" <td>13</td>\n",
|
||
|
|
" <td>40</td>\n",
|
||
|
|
" <td>77</td>\n",
|
||
|
|
" <td>60</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>47</th>\n",
|
||
|
|
" <td>70</td>\n",
|
||
|
|
" <td>18</td>\n",
|
||
|
|
" <td>84</td>\n",
|
||
|
|
" <td>26</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>48</th>\n",
|
||
|
|
" <td>97</td>\n",
|
||
|
|
" <td>22</td>\n",
|
||
|
|
" <td>24</td>\n",
|
||
|
|
" <td>34</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>49</th>\n",
|
||
|
|
" <td>56</td>\n",
|
||
|
|
" <td>83</td>\n",
|
||
|
|
" <td>9</td>\n",
|
||
|
|
" <td>95</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" </tbody>\n",
|
||
|
|
"</table>\n",
|
||
|
|
"</div>"
|
||
|
|
],
|
||
|
|
"text/plain": [
|
||
|
|
" f1 f2 f3 label\n",
|
||
|
|
"0 97 70 23 81\n",
|
||
|
|
"1 60 40 73 7\n",
|
||
|
|
"2 60 88 87 67\n",
|
||
|
|
"3 42 25 81 100\n",
|
||
|
|
"4 45 30 69 72\n",
|
||
|
|
"5 16 100 70 14\n",
|
||
|
|
"6 25 76 32 70\n",
|
||
|
|
"7 2 29 46 65\n",
|
||
|
|
"8 71 33 11 79\n",
|
||
|
|
"9 98 16 76 9\n",
|
||
|
|
"10 0 78 61 34\n",
|
||
|
|
"11 78 43 45 87\n",
|
||
|
|
"12 95 78 6 34\n",
|
||
|
|
"13 14 44 95 27\n",
|
||
|
|
"14 32 31 90 58\n",
|
||
|
|
"15 72 15 16 59\n",
|
||
|
|
"16 5 72 31 36\n",
|
||
|
|
"17 72 30 94 55\n",
|
||
|
|
"18 55 19 91 74\n",
|
||
|
|
"19 9 20 10 34\n",
|
||
|
|
"20 3 6 25 49\n",
|
||
|
|
"21 63 61 86 55\n",
|
||
|
|
"22 25 21 0 85\n",
|
||
|
|
"23 80 66 73 51\n",
|
||
|
|
"24 96 46 35 58\n",
|
||
|
|
"25 7 4 89 25\n",
|
||
|
|
"26 92 11 77 59\n",
|
||
|
|
"27 38 94 19 46\n",
|
||
|
|
"28 34 24 94 70\n",
|
||
|
|
"29 100 91 46 76\n",
|
||
|
|
"30 43 10 35 78\n",
|
||
|
|
"31 15 24 57 6\n",
|
||
|
|
"32 51 47 47 55\n",
|
||
|
|
"33 83 5 84 40\n",
|
||
|
|
"34 100 22 26 72\n",
|
||
|
|
"35 60 83 80 92\n",
|
||
|
|
"36 28 39 82 17\n",
|
||
|
|
"37 56 20 94 85\n",
|
||
|
|
"38 72 56 63 54\n",
|
||
|
|
"39 15 60 30 72\n",
|
||
|
|
"40 41 21 86 54\n",
|
||
|
|
"41 85 7 50 87\n",
|
||
|
|
"42 48 13 69 93\n",
|
||
|
|
"43 75 20 98 96\n",
|
||
|
|
"44 41 18 14 31\n",
|
||
|
|
"45 84 13 62 6\n",
|
||
|
|
"46 13 40 77 60\n",
|
||
|
|
"47 70 18 84 26\n",
|
||
|
|
"48 97 22 24 34\n",
|
||
|
|
"49 56 83 9 95"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 17,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"df"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 18,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"X = df[['f1','f2','f3']]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 21,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"y = df['label']"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 22,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"from sklearn.model_selection import train_test_split"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 23,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 24,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"(33, 3)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 24,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"X_train.shape"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 25,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"(17, 3)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 25,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"X_test.shape"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"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": "3.7.3"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 4
|
||
|
|
}
|