CheeseZH: Stanford University: Machine Learning Ex2:Logistic Regression

In Logisttic Regression, the hypothesis is defined as:

where function g is the sigmoid function. The sigmoid function is defined as:

2.Cost function and gradient

The cost function in logistic regression is:

the gradient of the cost is a vector of the same length as θ  where j^th element(for j=0,1,...,n) is defined as follows:

3. Regularized Cost function and gradient

Recall that the regularized cost function in logistic regression is:

The gradient of the cost function is a vector where the j^th element is defined as follows:

for j=0:

for j>=1:

 

Here are the code files:

ex2_data1.txt

 

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