特征提取/数据降维:PCA、LDA、MDS、LLE、TSNE等降维算法的python实现
Feature selector is a tool for dimensionality reduction of machine learning datasets
This is the Code for "Dimensionality Reduction - The Math of Intelligence #5" By Siraj Raval on Youtube
Using siamese network to do dimensionality reduction and similar image retrieval
Variational Autoencoder for Dimensionality Reduction of Time-Series
Dimensionality reduction in very large datasets using Siamese Networks
Deprecated in favor of MultivariateStats.jl
t-SNE dimensionality reduction technique for openFrameworks
An implementation of demixed Principal Component Analysis (a supervised linear dimensionality reduction technique)
Comparison of dimensionality reduction methods
Zero-inflated dimensionality reduction algorithm for single-cell data
Implementation of spectral dimensionality reduction algorithms (PCA, MDS, Difussion maps, LLE)
Twitter sentiment analysis part 8: Dimensionality reduction (chi-squared, PCA)
A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
General-purpose dimensionality reduction and manifold learning tool based on Variational Autoencoder, implemented in TensorFlow.
[CVPR2019] NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction
MATLAB code for dimensionality reduction, feature extraction, fault detection, and fault diagnosis using Kernel Principal Component Analysis (KPCA).
PyTorch Implementation of "NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction"
Common pre-processing in NLP such as PPMI computation, SVD-based dimensionality reduction, and PLSR-based distribution prediction.