Logistic Regression using matlab

Logistic Regression is one of the most famous classification algorithms, like Linear Regression we discussed before , it is easy to implement and gives great predictions.
The Logistic Regression algorithm has two major categories:

  • Binary-Class: where the result is 0 or 1 (belong to a certain class or not), an example of it is the spam email detection problem, where the result could be 0 (not spam), or 1 (spam). 
  • Multi-Class: where the result could be any value in the range (0..n), where n is the number of classes, an example of it it the handwritten digit recognition, where we have 10 classes (n = 10), each class represent a number between 0 and 9.
Implementing Binary-Class Logistic Regression using matlab is similar to implementing Linear Regression, with some modifications of the hypothesis and cost function formulas.

In this video, I implement the algorithm using matlab:


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