NO.Idea

Classification

Linear Classification#

Algorithms#

Logistic Regression#

In Logistic Regression, all we need to know is a sigmoind function, which scales our predictions to (0, 1) and its object function, which uses MLE to find the parameters. Object function is also the negative cross entropy. So we either use gradient ascent to update parameters using MLE or use gradient descent using cross entropy. People tend to use the latter one.

CODE

SVM#

KNN#

KMeans#

Decision Tree#

Random Forest#

Comparisons#

Linear Separable#