Category Archives: Scikit

I was looking at k-NN classification using the scikit library recently. While wading through the scikit documentation, I noticed that scikit has a closely related Radius Neighbors classifier module. When I did my k-NN example, I used the Wheat Seeds … 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 income of a person based on their sex, age, State, and political leaning. (Note: Somewhat confusingly, “logistic … Continue reading →

One of my work laptops died so I tried to reimage it by reinstalling everything, including OS, from the ground up. While that was going on, I decided to entertain myself by doing a k-nearest neighbors (k-NN) classification example using … Continue reading →

The scikit-learn library was originally designed for classical machine learning techniques like logistic regression and naive Bayes classification. The library eventually added the ability to do binary and multi-class classification via the MLPClassifier (multi-layer perceptron) class and regression via the … Continue reading →

The scikit-learn code library has a MultinomialNB class that can be used to create prediction models for multinomial data. The most common form of multinomial data has predictor variables where the values are counts. For example, suppose you want to … Continue reading →

I wrote an article titled “Binary Classification Using a scikit Decision Tree” in the February 2023 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2023/02/21/scikit-decision-tree.aspx. A decision tree is a machine learning technique that can be used for binary classification or … Continue reading →

The scikit-learn (aka scikit) library can do neural networks. In a work environment, I use PyTorch because it’s very flexible. But one morning, just for fun and mental exercise, I decided to create a scikit neural network multi-class classifier to … Continue reading →

Ah, where to begin. Bottom line: spectral clustering is a machine learning technique that is great in theory but just isn’t practical or useful in most real-world scenarios. The idea of clustering is to group data points together so that … Continue reading →

I was looking at logistic regression with the scikit-learn (scikit or sklearn for short) library. There is a built-in scikit confusion_matrix(y_actuals, y_predicteds) function to compute and display a confusion matrix. But the output of printing the result of confusion_matrix() isn’t … Continue reading →

I’ve been reviewing the scikit-learn (scikit for short) library for several months, so I figured I’d do a multi-class decision tree classification example. Before I go any further, let me comment that machine learning beginners are often seduced by the … Continue reading →