Category Archives: Scikit

I wrote an article titled “Logistic Regression Using the scikit Library” in the February 2023 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2023/02/01/scikit.aspx. Logistic regression is a machine learning technique for binary classification. For example, you might want to predict … Continue reading →

I was working with the scikit naive Bayes classifier. Naive Bayes is best used for categorical / string / text data such as a file that looks like: actuary green korea F barista green italy M dentist hazel japan M … Continue reading →

Naive Bayes classification is a classical machine learning technique. It is best used when the predictor variables are all non-numeric. Naive Bayes works for both binary classification and multi-class classification. And naive Bayes works well when you don’t have very … Continue reading →

I hadn’t looked at using a decision tree from the scikit-learn (scikit for short) library for several months, so I figured to do an example. Before I go any further: I am not a big fan of decision trees and … Continue reading →

It had been a while since I looked at logistic regression using the scikit-learn (scikit or sklearn for short) machine learning library. Like any kind of skill, it’s important to stay in practice. I used one of my standard datasets … Continue reading →