Dan McLinden

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

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.

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

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

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

The Tasmanian devil is endangered due to Devil Facial Tumour Disease (DFTD), a contagious cancer with no current treatment. Previous study has investigated the anticancer properties of Tasmanian devil cathelicidins. This report intends to reproduce the enrichment analysis results of the study and further analyze their data.

PCA and MDS analyses

M.Sc Data Science Related Works

Exploring Cybersecurity Data Science: Dimensionality Reduction and Cluster Analysis

Advanced Multivariate Statistics project

Partial Order Scalogram Analysis with Base Co-ordinates

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).

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