There are 5 repositories under multidimensional-scaling topic.
Introduction to Manifold Learning - Mathematical Theory and Applied Python Examples (Multidimensional Scaling, Isomap, Locally Linear Embedding, Spectral Embedding/Laplacian Eigenmaps)
Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)
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.
Analysis of Data Scientist Job Descriptions using Natural Language Processing
Unsupervised Learning
This routine is implemented in Matlab
UC Berkeley CUNEIF 102A (Sumerian Text Analysis) Fall 2017
Analyzing the historical cryptocurrency trading dataset, to portrait its dynamic landscape and dig into features of crypt currencies to figure out if any patterns in their price movement.
Showcasing Manifold Learning with ISOMAP, and compare the model to other transformations, such as PCA and MDS.
A physics-inspired R package for robust Euclidean embedding of sparse, non-metric dissimilarity data. Particularly powerful for antigenic cartography and viral evolution tracking, but applicable to any domain with incomplete similarity measurements. Published in *Bioinformatics* (2025).
This repository contains materials associated to the course "Multivariate Analysis" taught at the Faculty of Mathematics and Statistics (FME), UPC under the MESIO-UPC-UB Interuniversity Program under the instructors "Ferran Revertar", "Miguel Salicru" and "Jan Graffelman"
The code for Multidimensional Scaling (MDS), Sammon Mapping, and Isomap.
Using R & VoteView mutlidimensional scaling (MDS) methods for the analysis & visualization of complex patterns of crosslinguistic variation.
Experiments in NLOS mitigitation under MDS-based RF Positioning
A library for the Analysis of Molecular Dynamics Simulations of Self Assembling Peptides. Started during an internship at CNTE, Niguarda Hospital, Milan
Collective Project is one of our required courses for master degree in Mathematics which comprises of 5 members each. In this our group, we are working on Multidimensional Scaling: Multidimensional Scaling is a set of procedures that allows the researcher to map distances between objects in a multidimensional space into a lower-dimensional space in order to show how the objects are related.
Multidimensional Scaling using Cliques (MDS-Clique)
Framework to manage, prepare, train and evaluate models
hmds: An R Package for Heuristic High and Multi Dimensional Scaling
Dimensionality reduction and data embedding via PCA, MDS, and Isomap.
Word-alignment models for Bible translations in 100+ historical and contemporary languages
Neighbourhood-preserving dimension reduction via localised multidimensional scaling
lsp-python is a lightweight implementation of the least square projection (LSP) dimensionality reduction technique using a sklearn style API.
趨勢型資料偵測
A web application for experimenting with dimensionality reduction with human guidance.
M.Sc Data Science Related Works
Exploring Cybersecurity Data Science: Dimensionality Reduction and Cluster Analysis
An overview of my understanding of PCA for dimensionality reduction and Logistic Regression for model training and evaluation.
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).
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.
Grouping Social Media Influencers based on subscribers, views, likes, comments, and shares using Multidimensional Scaling (MDS)