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Logistic Regression Formulation
Given X, we want
Parameters:
Output (Activation):
Given [(x^{(1)}, y^{(1)}), (x^{(2)}, y^{(2)}), ..., (x^{(m)}, y^{(m)})], we want
If z is large positive,
If z is large negative,

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Data Science
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Learn After
Related
OLS fitting cannot be used for classification
Using LDA vs Logistic Regression
Logistic Regression Videos
Binary Classification Metrics
Hypothesis
Hypothesis function
Logistic Regression - Regularization
Linear Regression vs Logistic Regression
Softmax Regression (Activation)
Simple Logistic Regression Equation