06: Logistic Regression

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Classification
Hypothesis representation
Interpreting hypothesis output
Decision boundary
Decision boundary



Non-linear decision boundaries

Cost function for logistic regression

A convex logistic regression cost function

Simplified cost function and gradient descent

How to minimize the logistic regression cost function


Advanced optimization
Using advanced cost minimization algorithms

function [jval, gradent] = costFunction(THETA)
options= optimset('GradObj', 'on', 'MaxIter', '100'); % define the options data structure
initialTheta= zeros(2,1); # set the initial dimensions for theta % initialize the theta values
[optTheta, funtionVal, exitFlag]= fminunc(@costFunction, initialTheta, options); % run the algorithm

Multiclass classification problems