Ecosyste.ms: Repos

An open API service providing repository metadata for many open source software ecosystems.

GitHub topics: isomap

aperiodik/Macrophenological-dynamics-paper

data and R code to reproduce the analysis and plots presented in the manuscript: "Macrophenological dynamics from citizen science plant occurrence data"

Language: R - Size: 41.6 MB - Last synced: 3 days ago - Pushed: 3 days ago - Stars: 0 - Forks: 1

saehm/DruidJS

A JavaScript Library for Dimensionality Reduction

Language: JavaScript - Size: 6.15 MB - Last synced: 4 days ago - Pushed: 10 months ago - Stars: 105 - Forks: 9

GioStamoulos/Kmers_Dataset_Generation_Regression_Clustering

The generation of a kmers dataset that is associated with multiple gene sequences and the further manipulation of this generated dataset are the main contents of the current project.

Language: Jupyter Notebook - Size: 50.1 MB - Last synced: 26 days ago - Pushed: over 2 years ago - Stars: 3 - Forks: 0

wildart/ManifoldLearning.jl

A Julia package for manifold learning and nonlinear dimensionality reduction

Language: Julia - Size: 3.5 MB - Last synced: 22 days ago - Pushed: 3 months ago - Stars: 92 - Forks: 22

lowhung/naive-bayes-pca-mds

Implementations of MAP, Naive Bayes, PCA, MDS, ISOMAP and some compression

Language: Python - Size: 1.82 MB - Last synced: about 1 month ago - Pushed: almost 7 years ago - Stars: 3 - Forks: 0

mpolinowski/isometric-mapping

Non-linear dimensionality reduction through Isometric Mapping

Language: Jupyter Notebook - Size: 427 KB - Last synced: about 1 month ago - Pushed: about 1 year ago - Stars: 1 - Forks: 0

drewwilimitis/Manifold-Learning

Introduction to Manifold Learning - Mathematical Theory and Applied Python Examples (Multidimensional Scaling, Isomap, Locally Linear Embedding, Spectral Embedding/Laplacian Eigenmaps)

Language: Jupyter Notebook - Size: 140 MB - Last synced: 3 months ago - Pushed: about 4 years ago - Stars: 195 - Forks: 37

nikapotato/dimensionality-reduction

The key dimensionality reduction techniques: ISOMAP, PCA (Principal Component Analysis), and t-SNE (t-Distributed Stochastic Neighbor Embedding) are presented and compared.

Size: 1.77 MB - Last synced: 21 days ago - Pushed: 4 months ago - Stars: 0 - Forks: 0

alessimichele/Unsupervised-Learning-2023 Fork of ilariavascotto/Unsupervised-Learning-2023

This repository is dedicated to the lab activities of the course of Unsupervised Learning @UniTs

Language: Jupyter Notebook - Size: 82.6 MB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 0 - Forks: 0

bghojogh/MDS-SammonMapping-Isomap

The code for Multidimensional Scaling (MDS), Sammon Mapping, and Isomap.

Language: Python - Size: 89.2 MB - Last synced: 8 months ago - Pushed: over 3 years ago - Stars: 3 - Forks: 2

jgurakuqi/graph-kernels-and-manifold-svm

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.

Language: Jupyter Notebook - Size: 70.3 MB - Last synced: 7 months ago - Pushed: 10 months ago - Stars: 1 - Forks: 0

jonzia/Manifold

Manifold mapping with ISOMAP (MATLAB).

Language: MATLAB - Size: 12.7 KB - Last synced: 8 months ago - Pushed: about 3 years ago - Stars: 1 - Forks: 0

gionanide/Speech_Signal_Processing_and_Classification

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

Language: Python - Size: 827 KB - Last synced: 7 months ago - Pushed: over 1 year ago - Stars: 220 - Forks: 62

fratorgano/dimensionality-reduction

Project to learn a bit more about dimensionality reduction techniques

Language: Jupyter Notebook - Size: 74 MB - Last synced: 9 months ago - Pushed: about 3 years ago - Stars: 2 - Forks: 0

Sagarnandeshwar/Visualizing_High_Dimensional_Data

Applied Machine Learning (COMP 551) Course Project

Language: Jupyter Notebook - Size: 24.5 MB - Last synced: 10 months ago - Pushed: 10 months ago - Stars: 1 - Forks: 0

fsarab/MDS-ISOMAP

This project includes implementations of the MDS and ISOMAP algorithms using Python and various libraries such as NumPy, Matplotlib, Scikit-learn, and NetworkX.

Language: Jupyter Notebook - Size: 472 KB - Last synced: 4 months ago - Pushed: 10 months ago - Stars: 0 - Forks: 0

MJAHMADEE/VAE

Variational Autoencoder

Language: Jupyter Notebook - Size: 13.6 MB - Last synced: 11 months ago - Pushed: 11 months ago - Stars: 1 - Forks: 0

Sarvandani/Machine_learning_6_algorithms_of_dimensionality_reduction

Sklearn, PCA, t-SNE, Isomap, NMF, Random Projection, Spectral Embedding

Language: Jupyter Notebook - Size: 8.59 MB - Last synced: 11 months ago - Pushed: 11 months ago - Stars: 0 - Forks: 0

Smendowski/data-embedding-and-visualization

Visualization and embedding of large datasets using various Dimensionality Reduction (DR) techniques such as t-SNE, UMAP, PaCMAP & IVHD. Implementation of custom metrics to assess DR quality with complete explaination and workflow.

Language: Jupyter Notebook - Size: 177 MB - Last synced: 4 months ago - Pushed: almost 2 years ago - Stars: 1 - Forks: 0

matteo-serafino/dimensionality-reduction-package

Python package for plug and play dimensionality reduction techniques and data visualization in 2D or 3D.

Language: Python - Size: 34.2 KB - Last synced: 3 days ago - Pushed: about 1 year ago - Stars: 3 - Forks: 0

jasonfilippou/DimReduce

Implementations of 3 linear and non-linear dimensionality reduction algorithms

Language: Python - Size: 48.3 MB - Last synced: 10 months ago - Pushed: over 3 years ago - Stars: 3 - Forks: 1

mpolinowski/manifold-learning-for-image-segmentation

Use Manifold Learning, Mapping and Discriminant Analysis to Visualize Image Datasets

Language: Jupyter Notebook - Size: 4.34 MB - Last synced: about 1 month ago - Pushed: about 1 year ago - Stars: 1 - Forks: 0

svachmic-ctu/isomap

Example implementation of Isomap algorithm in R

Language: R - Size: 158 KB - Last synced: 6 months ago - Pushed: almost 8 years ago - Stars: 1 - Forks: 1

AAU-Dat/P5-Nonlinear-Dimensionality-Reduction

5th semester project concerning feature engineering and nonlinear dimensionality reduction in particular.

Language: Jupyter Notebook - Size: 47.3 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 1 - Forks: 2

tracy-talent/curriculum

a repository for my curriculum project

Language: Python - Size: 135 MB - Last synced: over 1 year ago - Pushed: over 1 year ago - Stars: 81 - Forks: 66

KodAgge/AdvancedMachineLearning

A collection of the assignments in the course advanced machine learning

Language: Python - Size: 2.23 MB - Last synced: 4 months ago - Pushed: over 2 years ago - Stars: 0 - Forks: 0

PyDimRed/PyDimRed

A comparison between some dimension reduction algorithms

Language: Jupyter Notebook - Size: 25.8 MB - Last synced: about 1 year ago - Pushed: over 5 years ago - Stars: 3 - Forks: 2

tejasnp163/Dimensionality-Reduction-on-Wine-Dataset

Performed different tasks such as data preprocessing, cleaning, classification, and feature extraction/reduction on wine dataset.

Language: Jupyter Notebook - Size: 5.44 MB - Last synced: about 1 year ago - Pushed: over 3 years ago - Stars: 3 - Forks: 0

tate8/dimensionality-reduction

Performing dimensionality reduction with various ML algorithms

Language: Jupyter Notebook - Size: 1.34 MB - Last synced: about 1 year ago - Pushed: over 2 years ago - Stars: 0 - Forks: 0

Pradnya1208/Dimensionality-Reduction-Techniques

The goal of this project is to understand and build various dimensionality reduction techniques.

Language: Jupyter Notebook - Size: 3.76 MB - Last synced: about 1 year ago - Pushed: over 2 years ago - Stars: 0 - Forks: 0

Daphilippe/brain_connectivity

Optimal transport for comparing short brain connectivity between individuals | Optimal transport | Wasserstein distance | Barycenter | K-medoids | Isomap| Sulcus | Brain

Language: Python - Size: 126 MB - Last synced: about 1 year ago - Pushed: almost 3 years ago - Stars: 0 - Forks: 0

mark-antal-csizmadia/pca-mds-isomap

Dimensionality reduction and data embedding via PCA, MDS, and Isomap.

Language: Jupyter Notebook - Size: 4.34 MB - Last synced: about 1 year ago - Pushed: almost 3 years ago - Stars: 0 - Forks: 0

chris-santiago/decomposition

Simple ISOMAP and PCA decomposition algorithms

Language: Python - Size: 7.81 KB - Last synced: about 1 year ago - Pushed: about 4 years ago - Stars: 1 - Forks: 0

Arijit1000/ISOMAP-implementation

The main objective of this project is dimensionality reduction. We do dimensional reduction for reducing memory size and complexity of the model.

Language: Jupyter Notebook - Size: 75.2 KB - Last synced: about 1 year ago - Pushed: about 3 years ago - Stars: 1 - Forks: 0

python3f/isomap

Isomap is a data visualisation technique based on geodesic distance.

Language: Jupyter Notebook - Size: 777 KB - Last synced: about 1 year ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0

Oliver-Binns/MLAP

Open Assessment for Machine Learning and Applications module. This assessment scored 83% and was worth 8 credits of my third year.

Language: TeX - Size: 2.26 MB - Last synced: over 1 year ago - Pushed: about 6 years ago - Stars: 0 - Forks: 0

vashistak/dimensionality-reduction-techniques

PYTHON PROGRAMMING

Language: Python - Size: 13.1 MB - Last synced: over 1 year ago - Pushed: over 7 years ago - Stars: 0 - Forks: 1

Related Keywords
isomap 37 pca 18 dimensionality-reduction 16 machine-learning 9 t-sne 8 manifold-learning 7 mds 6 lle 6 spectral-embedding 5 laplacian-eigenmaps 5 principal-component-analysis 5 python 5 umap 5 kernel-pca 5 clustering 4 multidimensional-scaling 3 locally-linear-embedding 3 manifold 3 lda 3 unsupervised-learning 3 sklearn 3 nlp 2 expectation-maximization 2 linear-discriminant-analysis 2 dimension-reduction 2 data-science 2 svd 2 factor-analysis 2 scikit-learn 2 random-projection 2 bilstm-crf 1 chart-parser 1 computational-theory 1 mnist 1 distributed-systems 1 logistic-regression 1 golang 1 feature-engineering 1 invertedindex 1 dimiensionality 1 dr 1 drquality 1 ivhd 1 knngain 1 metrics 1 pacmap 1 reduction 1 sheppard 1 trustworthiness 1 visualization 1 truncated-svd 1 cca 1 grassman-manifold 1 locality-sensitive-hashing 1 manifold-learning-algorithms 1 stiefel-manifold 1 fisher-discriminant-analysis 1 image-segmentation 1 algorithm 1 computer-vision 1 convolutional-neural-network 1 barycentre 1 brain 1 centroid 1 distance 1 k-medoids 1 optimal 1 sulcus 1 transport 1 wasserstein 1 data-embedding 1 decomposition 1 deep-learning 1 model-training 1 methods 1 optimization 1 em-algorithm 1 expectation-maximization-algorithm 1 lpp 1 facedete 1 mapreduce 1 ner 1 raft 1 reinforcement-learning 1 tensorflow 1 triangle-count 1 dag 1 eigen-decomposition 1 spectral-analysis 1 tree-graphs 1 variational-inference 1 eda 1 fda 1 knn-classification 1 pca-analysis 1 wine-dataset 1 mda 1 random-forest 1 barycenter 1 binary-data 1