PCA and MDS analyses

Dan McLinden

Performing Multidimensional Scaling with Gradient Descent and Gauss-Newton in JavaScript

This repo contains project(s) from the Marketing Analytics course.

Explore spaces of phylogenetic trees

Performing common visual data analytic tasks using Python and D3.js.

Applying data mining techniques to a set of documents to determine meaningful relationships between them.

Application of Multivariate Statistics on customer’ habits features to obtain a Customer segmentation of a wholesale shop.

Product Positioning by Semantic Network Analysis and multidimensional scaling

Advanced Multivariate Statistics project

A web application for experimenting with dimensionality reduction with human guidance.

Quadratic Programming with Complementarity Constraints

This project explores the spatial relationships between twenty European cities using classical manual Multidimensional Scaling (MDS), MDS from scikit-learn, and compares the results with Principal Component Analysis (PCA).

Multivariate data analysis using R Studio.

Using chaos game plots, dissimilarity matrices, and multidimensional scaling to observe distances between CRISPR genomic signatures.

Partial Order Scalogram Analysis with Base Co-ordinates

Multidimensional Scaling

In this project, I conduct MDS to analyze the similarity between Pokemon based on their base stats (also known as species strengths). Applying MDS, it is possible to plot Pokemon in a lower-dimensional space based on their species strengths: HP, attack, defense, special attack, special defense and speed. R programming language is used.

EDA and classification predictions of airline satisfaction using R

An overview of my understanding of PCA for dimensionality reduction and Logistic Regression for model training and evaluation.