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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"For each member of the dataset, the result (Y) determines which variation of the cost function is used. The Y = 0 cost function punishes high probability estimations, and Y = 1 punishes low scores. The \"punishment\" makes the change in the gradient of ThetaCurrent - Average(CostFunction(Dataset)) greater" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 11, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"def Cost_Function(X,Y,theta,m):\n", | |
" sumOfErrors = 0\n", | |
" for i in range(m):\n", | |
" xi = X[i]\n", | |
" hi = Hypothesis(theta,xi)\n", | |
" if Y[i] == 1:\n", | |
" error = Y[i] * math.log(hi)\n", | |
" elif Y[i] == 0:\n", | |
" error = (1-Y[i]) * math.log(1-hi)\n", | |
" sumOfErrors += error\n", | |
" const = -1/m\n", | |
" J = const * sumOfErrors\n", | |
" print('cost is ', J)\n", | |
" return J" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
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"name": "ipython", | |
"version": 3 | |
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"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.6.1" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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