Category Archives: Scikit

I spend 30 minutes each morning before work looking at technical stuff. One morning I decided to dissect the scikit library SpectralCustering module. Spectral clustering is much more complicated than the two most common techniques, k-means clustering and DBSCAN clustering. … Continue reading →

Poisson regression is a relatively rare form of machine learning where the goal is to predict a single numeric value in situations where the data is approximately Poisson distributed. An example of Poisson data is the number of customers who … Continue reading →

I wrote an article titled “Regression Using scikit Kernel Ridge Regression” in the July 2023 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2023/07/06/scikit-kernel-ridge-regression.aspx. A regression problem is one where the goal is to predict a single numeric value. For example, … Continue reading →

Four reasons that I rarely use decision trees for regression are characteristics of trees in general and apply to regression and classification: 1. Decision trees are highly unstable — a small change in the training data creates a completely different … Continue reading →

I wrote an article titled “Binary Classification Using a scikit Neural Network” in the June 2023 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2023/06/15/scikit-neural-network.aspx. A binary classification problem is one where the goal is to predict the value of a … Continue reading →

One Sunday morning, for no real reason I can think of, I decided to put together a demo of unsupervised anomaly detection using the scikit library k-means clustering module. The idea is simple. Take some source data and cluster it … Continue reading →

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 →