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68 search results found

Uniform Manifold Approximation and Projection

Machine Learning With Python ⭐ 2,980

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Awesome Community Detection ⭐ 2,232

A curated list of community detection research papers with implementations.

Minisom ⭐ 1,339

🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps

Opentsne ⭐ 1,295

Extensible, parallel implementations of t-SNE

Datasets ⭐ 521

A repository of pretty cool datasets that I collected for network science and machine learning research.

Minimum-distortion embedding with PyTorch

Dimensionality reduction in very large datasets using Siamese Networks

Machine Learning Notebooks ⭐ 241

Machine Learning notebooks for refreshing concepts.

Hierarchical Uniform Manifold Approximation and Projection

A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).

Go Tsne ⭐ 169

t-Distributed Stochastic Neighbor Embedding (t-SNE) in Go

The Data Science Workshop ⭐ 156

A New, Interactive Approach to Learning Data Science

Selfsne ⭐ 147

Self-Supervised Noise Embeddings (Self-SNE) for dimensionality reduction and clustering

Machine_learning_2018 ⭐ 146

Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz

Umap.jl ⭐ 115

Uniform Manifold Approximation and Projection (UMAP) implementation in Julia

Parametricumap_paper ⭐ 112

Parametric UMAP embeddings for representation and semisupervised learning. From the paper "Parametric UMAP: learning embeddings with deep neural networks for representation and semi-supervised learning" (Sainburg, McInnes, Gentner, 2020).

Walklets ⭐ 96

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

Hyperspectral_image_analysis_simplified ⭐ 77

The repository contains the implementation of different machine learning techniques such as classification and clustering on Hyperspectral and Satellite Imagery.

Local Fisher Discriminant Analysis in R

Topometry ⭐ 69

Systematically learn and evaluate manifolds from high-dimensional data

A PyTorch Implementation of "SINE: Scalable Incomplete Network Embedding" (ICDM 2018).

Covid19 Literature Clustering ⭐ 63

An approach to document exploration using Machine Learning. Let's cluster similar research articles together to make it easier for health professionals and researchers to find relevant research articles.

R package for Distance Metric Learning

Noise-Contrastive Visualization

Parallel Barnes-Hut t-SNE implementation written in Rust.

Clustershapley ⭐ 40

Explaining dimensionality results using SHAP values

2017 Spring (105-2) -- Machine Learning

Boostedfactorization ⭐ 31

An implementation of "Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation" (ASONAM 2019).

Competitive Feature Learning ⭐ 31

Online feature-extraction and classification algorithm that learns representations of input patterns.

R package for Tools for Handling Extraction of Features from Time series (theft)

NTUEE Machine Learning, 2017 Spring

An efficient symbolic time series approximation technique

Dynamicalcomponentsanalysis ⭐ 24

Dynamical Components Analysis

Encodermap ⭐ 24

python library for dimensionality reduction

Feature Selection using Metaheuristics Made Easy: Open Source MAFESE Library in Python

Keras Temporal Autoencoder ⭐ 23

Keras framework for autocovariance-based dimensionality reduction of time series data with deep neural networks.

Python+Rust implementation of the Probabilistic Principal Component Analysis model

A Python Library for Similarity-based Dimensionality Reduction

Machine_learning ⭐ 21

A repository of resources for understanding the concepts of machine learning/deep learning.

A fast, accurate, and modularized dimensionality reduction approach based on diffusion harmonics and graph layouts. Escalates to millions of samples on a personal laptop. Adds high-dimensional big data intrinsic structure to your clustering and data visualization workflow.

Recognize one of six human activities such as standing, sitting, and walking using a Softmax Classifier trained on mobile phone sensor data.

Data Science ⭐ 17

Utilizing Kaggle Data and Real-World Data for Data Science and Prediction in Python, R, Excel, Power BI, and Tableau.

Algorithmic framework for measuring feature importance, outlier detection, model applicability evaluation, and ensemble predictive modeling with (sparse) partial least squares regressions.

ADENINE: A Data ExploratioN PipelINE

Uncertainty-aware principal component analysis.

Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning

The biggest module developed with complete focus on Feature Selection (FS) using Meta-Heuristic Algorithm / Nature-inspired evolutionary / Swarm-based computing.

Predictive principal component analysis (PredPCA)

SNE Simulation Dataset Functions

Nystrompca ⭐ 11

Efficient non-linear PCA through kernel PCA with the Nyström method

Autoufstool ⭐ 10

Auto-UFSTool - An Automatic MATLAB Toolbox for Unsupervised Feature Selection

Customer Analytics ⭐ 10

Machine Learning Case study on customer segmentation and prediction of groups.

Fastlapmap ⭐ 9

Fast Laplacian Eigenmaps: lightweight multicore LE for non-linear dimensional reduction with minimal memory usage. Outperforms sklearn's implementation and escalates linearly beyond 10e6 samples.

Signal Processing ⭐ 9

Repository that gathers code for signal processing

SLISEMAP: Combining supervised dimensionality reduction with local explanations

Brainnet Ml Toolbox ⭐ 9

Python Machine Learning Toolbox for Brain Network Classification. Source codes are included of the top 20 teams in the Kaggle competition.

Country Profiling Using Pca And Clustering ⭐ 9

Unsupervised Machine Learning Analysis Using Clustering Model

Ml Algorithms On Scikit And Keras ⭐ 8

Implementation scripts of Machine Learning algorithms on Scikit-learn and Keras for complete novice..

A simple library for t-SNE animation and a zoom-in feature to apply t-SNE in that region

An open-source tool for performing feature selection process in different areas of research

Tensorflow2.0_notebooks ⭐ 6

Implementation of a series of Neural Network architectures in TensorFow 2.0

Kaggle Brainnetprediction Toolbox ⭐ 6

A Python toolbox for predicting brain network (graph) evolution over time from a single observation. The codes of the 20 competing Kaggle teams along with the competition datasets are made available.

Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning

Cancertherapy ⭐ 5

To use deep learning to identify patients whose tumor DNA mutations “look similar to” other tumors for which treatments are effective.

Dimensionality Reduction Pca ⭐ 5

Dimensionality reduction is basically a process of reducing the amount of random features,attributes variables or in this case called dimensions in a dataset and leaving as much variation in the dataset as possible by obtaining a set of only relevant features to increase the effiency of a model.

Binary Grey Wolf Optimization For Feature Selection ⭐ 5

Demonstration on how binary grey wolf optimization (BGWO) applied in the feature selection task.

Mycorrhiza Algorithm ⭐ 5

Combining phylogenetic networks and Random Forests for prediction of ancestry from multilocus genotype data

Neuralmap ⭐ 5

NeuralMap is a data analysis tool based on Self-Organizing Maps

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