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kernel-pca

Here are 42 public repositories matching this topic...

Albertsr / Anomaly-Detection

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

data-mining pca-analysis pca semi-supervised-learning principal-component-analysis intrusion-detection-system lof anomaly-detection isolation-forest mahalanobis-distance kernel-pca pulearning

Updated Feb 18, 2021
Python

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…

nlp classifier natural-language-processing feature-extraction nltk gaussian-mixture-models support-vector-machines mfcc principal-component-analysis speech-processing linear-discriminant-analysis isomap spectral-clustering long-short-term-memory kernel-pca spectral-embedding locally-linear-embedding linear-prediction-coefficients speech-utterance

Updated Mar 3, 2023
Python

Nikronic / Machine-Learning-Models

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

Updated Nov 7, 2021
Python

lucko515 / dataset-dimensionality-reduction-python

Here I've demonstrated how and why should we use PCA, KernelPCA, LDA and t-SNE for dimensionality reduction when we work with higher dimensional datasets.

machine-learning pca dimensionality-reduction lda tsne kernel-pca

Updated Jul 24, 2017
Jupyter Notebook

kaur-anupreet / Software-Defect-Prediction

Application of Deep Learning and Feature Extraction in Software Defect Prediction

python deep-neural-networks deep-learning decision-trees linear-discriminant-analysis principle-component-analysis kernel-pca

Updated Mar 25, 2020
Python

mlesnoff / rchemo

Archived repo (see Readme) - R package for regression and discrimination, with special focus on chemometrics and high-dimensional data.

Updated Apr 7, 2023
R

kashefy / mi2notes

My notes for Prof. Klaus Obermayer's "Machine Intelligence 2 - Unsupervised Learning" course at the TU Berlin

hmm kde clustering som pca expectation-maximization lle mixture-model density-estimation ica kernel-pca

Updated Mar 23, 2023
TeX

bghojogh / Principal-Component-Analysis

The code for Principal Component Analysis (PCA), dual PCA, Kernel PCA, Supervised PCA (SPCA), dual SPCA, and Kernel SPCA

kernel-methods principal-component-analysis kernel-pca supervised-pca dual-pca kernel-supervised-pca

Updated Nov 18, 2023
Python

mlesnoff / rnirs

Archived repo - This R Package is not developed anymore (only maintenance). It was replaced by R package rchemo

Updated Apr 7, 2023
R

OleguerCanal / GPLVM

Re-Implementation of GPLVM algorithm & performance assessment against Kernel-PCA

machine-learning pca dimensionality-reduction kernel-pca gplvm

Updated Jul 6, 2023
Python

juyongjiang / VFedPCA-VFedAKPCA

Source Code & Datasets for "Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data"

pca kernel-pca federated-learning feature-wise advanced-kernel-pca

Updated May 20, 2022
Python

MaxenceGiraud / BayesianPCA

Implementation of Bayesian PCA [Bishop][1999] And Bayesian Kernel PCA

pca bishop probabilistic-pca ppca kernel-pca bayesian-pca probabilistic-kernel-pca bayesian-kernel-pca pkpca bkpca bpca

Updated Jan 13, 2021
Python

namanUIUC / NonlinearComponentAnalysis

Application of principal component analysis capturing non-linearity in the data using kernel approach

kernel matlab svm nonlinear pca-analysis pca uiuc kernel-methods principal-component-analysis svm-classifier iris-dataset kernel-pca principal-component-analysis-pca

Updated Dec 29, 2018
Jupyter Notebook

tejasnp163 / Dimensionality-Reduction-on-Wine-Dataset

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

fda eda pca-analysis pca t-sne lda lle isomap knn-classification kernel-pca laplacian-eigenmaps wine-dataset

Updated Nov 2, 2020
Jupyter Notebook

ratvec / ratvec

Low-dimensional vector representations via kernel PCA with rational kernels

nlp machine-learning bioinformatics proteomics kernel-methods representation-learning kernel-pca

Updated Jan 7, 2020
Python

bghojogh / Image-Structural-Component-Analysis

The code for Image Structural Component Analysis (ISCA) and Kernel ISCA

ssim principal-component-analysis kernel-pca structural-similarity-index

Updated Jun 12, 2020
Python

matteo-serafino / dimensionality-reduction-package

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

clustering pca dimensionality-reduction t-sne mds lda factor-analysis umap isomap kernel-pca truncated-svd

Updated Apr 10, 2023
Python

hellpanderrr / ml_algorithms

Machine learning algorithms done from scratch in Python with Numpy/Scipy

python numpy pca scipy dimensionality-reduction clustering-algorithm kmeans-clustering kernel-kmeans kernel-pca

Updated Oct 10, 2018
Jupyter Notebook

charumakhijani / machine-learning

Data Science Portfolio

machine-learning random-forest clustering linear-regression pca dimensionality-reduction lda regression-models decision-tree principal-component-analysis linear-discriminant-analysis hierarchical-clustering k-means-clustering classification-model kernel-pca

Updated Feb 24, 2020
Jupyter Notebook

Arminkhayati / Machine_learning_lec

My Machine Learning course projects

python machine-learning machine-learning-algorithms tic-tac-toe ensemble-learning adaboost decision-tree decision-tree-classifier function-approximation m1 regressor bagging decision-tree-regression kpca kernel-pca kernel-knn

Updated Sep 12, 2021
Jupyter Notebook

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