Kernel tricks and nonlinear dimensionality reduction via RBF kernel PCA
The focus of this article is to briefly introduce the idea of kernel methods and to implement a Gaussian radius basis function (RBF) kernel that is used to…
Machine Learning
Machine Learning
Machine Learning
Predictive modeling, supervised machine learning, and pattern classification
When I was working on my next pattern classification application, I realized that it might be worthwhile to take a step back and look at the big picture of…
Machine Learning, python
Linear Discriminant Analysis
I received a lot of positive feedback about the step-wise Principal Component Analysis (PCA) implementation. Thus, I decided to write a little follow-up…
Machine Learning, python
About Feature Scaling and Normalization
I received a couple of questions in response to my previous article (Entry point: Data) where people asked me why I used Z-score standardization as feature…
Machine Learning, python
Entry Point Data
In this short tutorial I want to provide a short overview of some of my favorite Python tools for common procedures as entry points for general pattern…
Machine Learning, python, statistics
Implementing a Principal Component Analysis (PCA)
In this article I want to explain how a Principal Component Analysis (PCA) works by implementing it in Python step by step. At the end we will compare the…