ENSEMBLE CLASSIFIERS

Hello, welcome to my blog. Recently, I have been talking about two algorithms for classification namely logistic regression & decision trees. I also demonstrated how we can implement these algorithms using Python’s scikit-learn library.

Today, I want to talk about Ensemble classifiers. The fundamental idea behind ensemble classifiers is combining a set of classifiers to make one better classifier. Concretely, an ensemble classifier combines two or more classifiers (also called a weak learner or classifier) in order to make a stronger classifier (also called a strong learner or classifier). 

IMPLEMENTING DECISION TREES WITH PYTHON

Hello, welcome to my blog. In my previous post I introduced another classification algorithm called decision trees. In this post I want to demonstrate how to implement decision trees using the scikit-learn library in Python.

DECISION TREES

Hello, welcome to my blog. Recently, I have been talking about classification. I have talked about a linear classifier, how to use logistic regression to learn coefficients for a linear classifier. Furthermore, I demonstrated how to implement logistic regression using the sci-kit learn library in Python and I talked about evaluation metrics for classifiers.