This project includes implementations of the MDS and ISOMAP algorithms using Python and various libraries such as NumPy, Matplotlib, Scikit-learn, and NetworkX.
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Updated
Aug 4, 2023 - Jupyter Notebook
This project includes implementations of the MDS and ISOMAP algorithms using Python and various libraries such as NumPy, Matplotlib, Scikit-learn, and NetworkX.
Sklearn, PCA, t-SNE, Isomap, NMF, Random Projection, Spectral Embedding
data and R code to reproduce the analysis and plots presented in the manuscript: "Macrophenological dynamics from citizen science plant occurrence data"
Exploring Cybersecurity Data Science: Dimensionality Reduction and Cluster Analysis
Open Assessment for Machine Learning and Applications module. This assessment scored 83% and was worth 8 credits of my third year.
The key dimensionality reduction techniques: ISOMAP, PCA (Principal Component Analysis), and t-SNE (t-Distributed Stochastic Neighbor Embedding) are presented and compared.
My assignments for homework of Computational Data Mining course at Amirkabir University of Technology
Messing around with isometric rendering of tilemaps
Data analysis using Principal Component Analysis (PCA), Eigenvalues, Covariance matrix, Maximum Likelihood Estimation (MLE), ISOMAP, & Image recognition
A collection of the assignments in the course advanced machine learning
This repository is dedicated to the lab activities of the course of Unsupervised Learning @Units
Dimensionality reduction and data embedding via PCA, MDS, and Isomap.
Isomap is a data visualisation technique based on geodesic distance.
Applied Machine Learning (COMP 551) Course Project
Optimal transport for comparing short brain connectivity between individuals | Optimal transport | Wasserstein distance | Barycenter | K-medoids | Isomap| Sulcus | Brain
Example implementation of Isomap algorithm in R
Manifold mapping with ISOMAP (MATLAB).
This project aims to compare the performance obtained using a linear Support Vector Machine model whose data was first processed through a Shortest Path kernel with the same SVM, this time with data also processed by two alternative Manifold Learning techniques: Isomap and Spectral Embedding.
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