Statistical Machine Intelligence & Learning Engine

Comparison-based Machine Learning in Python

This module allows users to analyze k-means & hierarchical clustering, and visualize results of Principal Component, Correspondence Analysis, Discriminant analysis, Decision tree, Multidimensional scaling, Multiple Factor Analysis, Machine learning, and Prophet analysis.

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

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

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).

Product Positioning by Semantic Network Analysis and multidimensional scaling

EDA and classification predictions of airline satisfaction using R

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.

A library for the Analysis of Molecular Dynamics Simulations of Self Assembling Peptides. Started during an internship at CNTE, Niguarda Hospital, Milan

Advanced Multivariate Statistics project

Simplified 3D DIffusion Model Simulation for Organization of Programming Languages Fall 2022.

Multidimensional Scaling using Cliques (MDS-Clique)

趨勢型資料偵測

Word-alignment models for Bible translations in 100+ historical and contemporary languages

Multivariate data analysis using R Studio.

App for fast NMDS plots

Using R & VoteView mutlidimensional scaling (MDS) methods for the analysis & visualization of complex patterns of crosslinguistic variation.

PCA and MDS analyses