Category Archives: Scikit

I wrote an article titled “Gaussian Naive Bayes Classification Using the scikit Library” in the June 2023 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2023/05/31/gaussian-naive-bayes.aspx. Gaussian naive Bayes classification is a classical machine learning technique that can be used to … Continue reading →

A regression problem is one where the goal is to predict a single numeric value. A classic example is based on the Boston Area House dataset. The problem is to predict the median price of a house in one of … Continue reading →

I’ve been looking at Gaussian process regression (GPR) recently. There are several libraries available for GPR. GPR is very complex. Overall, the scikit library has pretty good documentation. But the documentation for the scikit GaussianProcessRegressor module is quite weak in … Continue reading →

A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the annual income of a person based on their sex (male or female), age, State of residence, and … Continue reading →

I experimented with a machine learning technique I haven’t seen used before. I used principal component analysis (PCA) to reduce the number of predictor variables in the training data, and then I used the reduced data to train a Gaussian … Continue reading →

The goal of a regression problem is to predict a single numeric value. For example, you might want to predict the selling price of a house based on its square footage, number of bedrooms, age, and so on. The simplest … Continue reading →

I was presenting a talk recently. One of my examples used the scikit-learn code library for machine learning. One of the attendees asked about the difference between “scikit” and “scikit-learn”. Briefly, scikit-learn is a Python language code library for machine … Continue reading →

Briefly, I put together a demo of a scikit Gaussian process regression model that uses the polynomial kernel from the sklearn.metrics.pairwise module via the PairwiseKernel class. Whew, what a mouthful. A Gaussian process regressor model predicts a single numeric value … Continue reading →