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ashutoshsahu2015/Probability Ratio Encoding.ipynb

Created March 20, 2021 08:07
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Probability Ratio Encoding.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 5,
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Survived</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Cabin</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>A</th>\n",
" <td>0.466667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>B</th>\n",
" <td>0.744681</td>\n",
" </tr>\n",
" <tr>\n",
" <th>C</th>\n",
" <td>0.593220</td>\n",
" </tr>\n",
" <tr>\n",
" <th>D</th>\n",
" <td>0.757576</td>\n",
" </tr>\n",
" <tr>\n",
" <th>E</th>\n",
" <td>0.750000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>F</th>\n",
" <td>0.615385</td>\n",
" </tr>\n",
" <tr>\n",
" <th>G</th>\n",
" <td>0.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>M</th>\n",
" <td>0.299854</td>\n",
" </tr>\n",
" <tr>\n",
" <th>T</th>\n",
" <td>0.000000</td>\n",
" </tr>\n",
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"text/plain": [
" Survived\n",
"Cabin \n",
"A 0.466667\n",
"B 0.744681\n",
"C 0.593220\n",
"D 0.757576\n",
"E 0.750000\n",
"F 0.615385\n",
"G 0.500000\n",
"M 0.299854\n",
"T 0.000000"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"prob=dataset.groupby(['Cabin'])['Survived'].mean()\n",
"prob_df=pd.DataFrame(prob)\n",
"prob_df"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Survived</th>\n",
" <th>Died</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Cabin</th>\n",
" <th></th>\n",
" <th></th>\n",
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" <tbody>\n",
" <tr>\n",
" <th>A</th>\n",
" <td>0.466667</td>\n",
" <td>0.533333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>B</th>\n",
" <td>0.744681</td>\n",
" <td>0.255319</td>\n",
" </tr>\n",
" <tr>\n",
" <th>C</th>\n",
" <td>0.593220</td>\n",
" <td>0.406780</td>\n",
" </tr>\n",
" <tr>\n",
" <th>D</th>\n",
" <td>0.757576</td>\n",
" <td>0.242424</td>\n",
" </tr>\n",
" <tr>\n",
" <th>E</th>\n",
" <td>0.750000</td>\n",
" <td>0.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>F</th>\n",
" <td>0.615385</td>\n",
" <td>0.384615</td>\n",
" </tr>\n",
" <tr>\n",
" <th>G</th>\n",
" <td>0.500000</td>\n",
" <td>0.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>M</th>\n",
" <td>0.299854</td>\n",
" <td>0.700146</td>\n",
" </tr>\n",
" <tr>\n",
" <th>T</th>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Survived Died\n",
"Cabin \n",
"A 0.466667 0.533333\n",
"B 0.744681 0.255319\n",
"C 0.593220 0.406780\n",
"D 0.757576 0.242424\n",
"E 0.750000 0.250000\n",
"F 0.615385 0.384615\n",
"G 0.500000 0.500000\n",
"M 0.299854 0.700146\n",
"T 0.000000 1.000000"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"prob_df['Died']=1-prob_df['Survived']\n",
"prob_df"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Survived</th>\n",
" <th>Died</th>\n",
" <th>Probability Ratio</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Cabin</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>A</th>\n",
" <td>0.466667</td>\n",
" <td>0.533333</td>\n",
" <td>0.875000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>B</th>\n",
" <td>0.744681</td>\n",
" <td>0.255319</td>\n",
" <td>2.916667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>C</th>\n",
" <td>0.593220</td>\n",
" <td>0.406780</td>\n",
" <td>1.458333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>D</th>\n",
" <td>0.757576</td>\n",
" <td>0.242424</td>\n",
" <td>3.125000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>E</th>\n",
" <td>0.750000</td>\n",
" <td>0.250000</td>\n",
" <td>3.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>F</th>\n",
" <td>0.615385</td>\n",
" <td>0.384615</td>\n",
" <td>1.600000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>G</th>\n",
" <td>0.500000</td>\n",
" <td>0.500000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>M</th>\n",
" <td>0.299854</td>\n",
" <td>0.700146</td>\n",
" <td>0.428274</td>\n",
" </tr>\n",
" <tr>\n",
" <th>T</th>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Survived Died Probability Ratio\n",
"Cabin \n",
"A 0.466667 0.533333 0.875000\n",
"B 0.744681 0.255319 2.916667\n",
"C 0.593220 0.406780 1.458333\n",
"D 0.757576 0.242424 3.125000\n",
"E 0.750000 0.250000 3.000000\n",
"F 0.615385 0.384615 1.600000\n",
"G 0.500000 0.500000 1.000000\n",
"M 0.299854 0.700146 0.428274\n",
"T 0.000000 1.000000 0.000000"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"prob_df['Probability Ratio']=prob_df['Survived']/prob_df['Died']\n",
"prob_df"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'A': 0.875,\n",
" 'B': 2.916666666666666,\n",
" 'C': 1.4583333333333333,\n",
" 'D': 3.125,\n",
" 'E': 3.0,\n",
" 'F': 1.6000000000000003,\n",
" 'G': 1.0,\n",
" 'M': 0.42827442827442824,\n",
" 'T': 0.0}"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"prob_encod_dictionary=prob_df['Probability Ratio'].to_dict()\n",
"prob_encod_dictionary"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Survived</th>\n",
" <th>Cabin</th>\n",
" <th>Cabin_probabilty_ratio</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0</td>\n",
" <td>M</td>\n",
" <td>0.428274</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>C</td>\n",
" <td>1.458333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1</td>\n",
" <td>M</td>\n",
" <td>0.428274</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1</td>\n",
" <td>C</td>\n",
" <td>1.458333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0</td>\n",
" <td>M</td>\n",
" <td>0.428274</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Survived Cabin Cabin_probabilty_ratio\n",
"0 0 M 0.428274\n",
"1 1 C 1.458333\n",
"2 1 M 0.428274\n",
"3 1 C 1.458333\n",
"4 0 M 0.428274"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset['Cabin_probabilty_ratio']=dataset['Cabin'].map(prob_encod_dictionary)\n",
"dataset.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
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