principal-component-analysis 开源项目推荐（1,269 个）

MaxHalford /prince

：Crown：Python中的多元探索性数据分析- PCA、CA、MCA、MFA、FAMD、GMA

nsoojin /coursera-ml-py

Coursera 上 Andrew Ng 教授的机器学习 Python 编程作业

abess-team /abess

快速最佳子集选择库

jayshah19949596 /Machine-Learning-Models

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

erdogant /pca

pca: A Python Package for Principal Component Analysis.

Albertsr /Anomaly-Detection

UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.

gionanide /Speech_Signal_Processing_and_Classification

前端语音处理旨在从语音话语的短期片段中提取适当的特征，这些片段称为框架。它是解决任何使用语音或音频（如音乐）模式识别问题的前提步骤。这里，我们关注声音障碍的分类。也就是说，开发两类分类器，能够区分例如声带麻痹患者和健康受试者的话语。人类语音产生系统的数学建模表明，全极系统功能是合理的[1-3]。因此，线性预测系数（LPC）成为建模语音短期频谱幅度的首选。LPC导出的中空系数保证区分系统（如声道）贡献与激发贡献。考虑到人耳特性，mel频率的中频频分相系数（MFCC）成为语音频谱包络的描述特征。与MFCCC类似，感知线性预测系数（PLP）也可以推导。上述说话传统特征将与由交集神经网络（CNN）（例如自编码器）提取的不可知性特征进行测试[4]。模式识别步骤将基于高斯混合模型分类器、K最近邻分类器、贝叶斯分类器以及深度神经网络。马萨诸塞州眼耳医院数据集（MEEI-Dataset）[5]将被利用。在应用层面，将开发一个用于Python特征提取和分类的库。可信的公开资源将被用于实现我们的目标，比如KALDI。将与[6-8]进行比较。

zavtech /morpheus-core

The foundational library of the Morpheus data science framework

arnaldog12 /Machine_Learning

Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

dlaptev /RobustPCA

Robust PCA implementation and examples (Matlab)

faridcher /ml-course

该项目在 GitHub 上没有填写描述

lestercardoz11 /fault-detection-for-predictive-maintenance-in-industry-4.0

This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.

bwlewis /irlba

Fast truncated singular value decompositions

erichson /ristretto

Randomized Dimension Reduction Library

Hassaan-Elahi /Writing-Styles-Classification-Using-Stylometric-Analysis

✍️ An intelligent system that takes a document and classifies different writing styles within the document using stylometric techniques.

tiskw /random-fourier-features

用于核方法的随机傅里叶特征实现，如支持向量机和高斯过程模型

erichson /rSVD

Randomized Matrix Decompositions using R

davircarvalho /Individualized_HRTF_Synthesis

Synthesis of individualized HRTFs based on Neural Networks, Principal Component Analysis and anthropometry

MaksimEkin /COVID19-Literature-Clustering

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.

hiroyuki-kasai /ClassifierToolbox

分类器的 MATLAB 工具箱：版本 1.0.7