kernel-pca

There are 1 repository under kernel-pca topic.

Albertsr / Anomaly-Detection
UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.
isolation-forest kernel-pca lof pulearning anomaly-detection principal-component-analysis intrusion-detection-system mahalanobis-distance pca-analysis semi-supervised-learning data-mining pca
Language:Python 263
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].
speech-processing mfcc linear-prediction-coefficients classifier speech-utterance feature-extraction support-vector-machines gaussian-mixture-models long-short-term-memory principal-component-analysis kernel-pca linear-discriminant-analysis isomap locally-linear-embedding spectral-embedding spectral-clustering natural-language-processing nlp nltk
Language:Python 230
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.
reinforcement-learning nlp-machine-learning pca apriori eclat upper-confidence-bound thompson-sampling lda kernel-pca xgboost linear-regression support-vector-regression logistic-regression k-nn svm naive-bayes random-forest decision-tree ann cnn
Language:Python 31
kaur-anupreet / Software-Defect-Prediction
Application of Deep Learning and Feature Extraction in Software Defect Prediction
decision-trees deep-learning deep-neural-networks kernel-pca linear-discriminant-analysis principle-component-analysis python
Language:Python 19
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.
pca tsne machine-learning lda dimensionality-reduction kernel-pca
Language:Jupyter Notebook 19
bghojogh / Principal-Component-Analysis
The code for Principal Component Analysis (PCA), dual PCA, Kernel PCA, Supervised PCA (SPCA), dual SPCA, and Kernel SPCA
dual-pca kernel-methods kernel-pca kernel-supervised-pca principal-component-analysis supervised-pca
Language:Python 14
mlesnoff / rchemo
Archived repo (see Readme) - R package for regression and discrimination, with special focus on chemometrics and high-dimensional data.
dimension-reduction discrimination chemometrics knn regression-models lwplsr kernel-methods ridge-regression pca partial-least-squares-regression non-linear-regression plsda latent-variable-models lwplsda svm signal-processing ridge-discrimination kernel-pca fda spectroscopy
Language:R 14
kashefy / mi2notes
My notes for Prof. Klaus Obermayer's "Machine Intelligence 2 - Unsupervised Learning" course at the TU Berlin
pca hmm expectation-maximization ica som mixture-model density-estimation kde kernel-pca clustering lle
Language:TeX 13
mlesnoff / rnirs
Archived repo - This R Package is not developed anymore (only maintenance). It was replaced by R package rchemo
regression discrimination chemometrics plsda lwplsr signal-processing pca pcr fda latent-variable-models cross-validation ridge partial-least-squares-regression svm-model svm knn kernel-pls kernel-ridge kernel-pca lwplsda
Language:R 11
OleguerCanal / GPLVM
Re-Implementation of GPLVM algorithm & performance assessment against Kernel-PCA
dimensionality-reduction gplvm kernel-pca machine-learning pca
Language:Python 11
juyongjiang / VFedPCA-VFedAKPCA
Source Code & Datasets for "Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data"
federated-learning feature-wise pca kernel-pca advanced-kernel-pca
Language:Python 10
MaxenceGiraud / BayesianPCA
Implementation of Bayesian PCA [Bishop][1999] And Bayesian Kernel PCA
pca bayesian-pca bishop probabilistic-pca kernel-pca probabilistic-kernel-pca bayesian-kernel-pca pkpca bkpca bpca ppca
Language:Python 8
namanUIUC / NonlinearComponentAnalysis
Application of principal component analysis capturing non-linearity in the data using kernel approach
pca-analysis kernel kernel-methods kernel-pca svm svm-classifier pca iris-dataset uiuc matlab principal-component-analysis principal-component-analysis-pca nonlinear
Language:Jupyter Notebook 8
ratvec / ratvec
Low-dimensional vector representations via kernel PCA with rational kernels
representation-learning kernel-methods kernel-pca bioinformatics nlp machine-learning proteomics
Language:Python 4
tejasnp163 / Dimensionality-Reduction-on-Wine-Dataset
Performed different tasks such as data preprocessing, cleaning, classification, and feature extraction/reduction on wine dataset.
knn-classification pca lda t-sne isomap lle fda wine-dataset kernel-pca pca-analysis laplacian-eigenmaps eda
Language:Jupyter Notebook 4
bghojogh / Image-Structural-Component-Analysis
The code for Image Structural Component Analysis (ISCA) and Kernel ISCA
ssim structural-similarity-index principal-component-analysis kernel-pca
Language:Python 3
matteo-serafino / dimensionality-reduction-package
Python package for plug and play dimensionality reduction techniques and data visualization in 2D or 3D.
dimensionality-reduction clustering factor-analysis isomap kernel-pca lda mds pca t-sne truncated-svd umap
Language:Python 3
AAU-Dat / P5-Nonlinear-Dimensionality-Reduction
5th semester project concerning feature engineering and nonlinear dimensionality reduction in particular.
computer-vision dimensionality-reduction feature-engineering machine-learning mnist convolutional-neural-network isomap kernel-pca linear-discriminant-analysis logistic-regression principal-component-analysis
Language:Jupyter Notebook 2
Arminkhayati / Machine_learning_lec
My Machine Learning course projects
machine-learning python machine-learning-algorithms function-approximation tic-tac-toe decision-tree-classifier decision-tree-regression regressor decision-tree bagging adaboost m1 ensemble-learning kernel-knn kernel-pca kpca
Language:Jupyter Notebook 2
charumakhijani / machine-learning
Data Science Portfolio
decision-tree random-forest regression-models classification-model clustering k-means-clustering hierarchical-clustering dimensionality-reduction pca principal-component-analysis kernel-pca lda linear-discriminant-analysis machine-learning linear-regression
Language:Jupyter Notebook 2
algostatml / UNSUPERVISED-ML
Unsupervised machine learning algorithm. Classical and kernel methods for non-linearly seperable data.
kernel-methods pca principal-component-analysis kmeans-clustering kernel-kmeans kernel-pca
Language:Python 1
EthanJamesLew / PSU_STAT672
Notes, homework and project for PSU's STAT 672 Winter 2020
pca kernel-pca clustering kernel-kmeans machine-learning gaussian-processes mvn lyapunov-functions
Language:Jupyter Notebook 1
hellpanderrr / ml_algorithms
Machine learning algorithms done from scratch in Python with Numpy/Scipy
clustering-algorithm dimensionality-reduction pca kmeans-clustering kernel-pca kernel-kmeans python numpy scipy
Language:Jupyter Notebook 1
Joycechidi / MachineLearning2
Continuation of my machine learning works based on Subjects....starting with Evaluating Classification Models Performance
clustering eval-classification-models-perf k-means-clustering hierarchical-clustering association-rule-learning apriori eclat reinforcement-learning upper-confidence-bound-ucb thompson-sampling natural-language-processing natural-language-processing-algo deep-learning artificial-neural-networks-ann convolutional-neural-networks-cnn dimensionality-reduction principal-component-analysis-pca linear-discriminant-analysis-lda kernel-pca model-selection--xgboost
1
kyomangold / ETH-MachineLearning
Repository for the code of the "Introduction to Machine Learning" (IML) lecture at the "Learning & Adaptive Systems Group" at ETH Zurich.
autoencoders expectation-maximization gaussian-bayesian-networks gaussian-mixture-models generative-adversarial-network k-means-clustering kernel-methods kernel-pca linear-regression logistic-regression maximum-a-posteriori-estimation maximum-likelihood-estimation naive-bayes-classifier neural-networks principal-component-analysis unsupervised-learning
Language:Python 1
longhongc / CMSC828C-hw6
K-means, Spectral clustering, PCA, and Kernel PCA
k-means kernel-pca pca spectral-clustering
Language:Jupyter Notebook 1
BeataWereszczynska / UML_forged_banknotes
UML dimensionality reduction and clustering models for predicting if a banknote is genuine or not based on the dataset from OpenML containing wavelet analysis results for genuine and forged banknotes - practical exercise. (Python 3)
agglomerative-clustering banknote-authentication banknote-forgery banknotes-authenticity clustering dbscan dbscan-clustering dimension-reduction dimensionality-reduction jupyter-notebook k-means k-means-clustering kernel-pca python python3 tsne unsupervised-learning unsupervised-machine-learning wavelet-analysis wavelets
Language:Jupyter Notebook 0
kisoo95 / DACON-Monthly-DACON-Credit-Card-Fraud-Deal-Detection-AI-Competition
Winning one of the DACON competition
dacon isolation-forest kernel-pca pacmap
Language:Jupyter Notebook 0
mohammad95labbaf / UMAP_breast_cancer
This repository explores the interplay between dimensionality reduction techniques and classification algorithms in the realm of breast cancer diagnosis. Leveraging the Breast Cancer Wisconsin dataset, it assesses the impact of various methods, including PCA, Kernel PCA, LLE, UMAP, and Supervised UMAP, on the performance of a Decision Tree.
breast-cancer-wisconsin decision-tree decision-tree-classifier dimensionality-reduction dimensionality-reduction-technique eda expolatory-data-analysis kernel-pca lle locally-linear-embedding principal-component-analysis umap
Language:Jupyter Notebook 0
shubhams821 / ML-Repository
Machine Learning assignments from coursework.
kernel-pca kmeans-clustering pca-analysis
Language:Jupyter Notebook 0
vitthal-bhandari / High-Dimensional-Data-and-Gradient-Descent
Analyzing and overcoming the curse of dimensionality and exploring various gradient descent techniques with implementations in R
curse-of-dimensionality-solution pca-analysis kernel-pca svd-matrix-factorisation gradient-descent stochastic-gradient-descent mini-batch-gradient-descent batch-gradient-descent
Language:HTML 0
williamagyapong / data-mining-projects
Houses a series of projects I worked on for a course in Data Mining that I took in my Ph.D. Data Science program at UTEP in the Fall of 2022. Covers areas such as Regularized Logistic Regression, Optimization, Kernel Methods, PageRank, Kernel PCA, Association Rule Mining, Anomaly Detection, Parametric/Nonparametric Nonlinear Regression, etc.
anomaly-detection association-rule-mining kernel-methods kernel-pca pagerank regression regression-splines regularized smoothing-splines artificial-neural-networks gam generalized-additive-models mars multivariate-adaptive-regression-splines random-forest support-vector-machines nonparametric-nonlinear-regression parametric-nonlinear-regression projection-pursuit-regression
0
Abhishek-Nalawade / Kernel-PCA
pca kernel-pca
Language:Python
alessimichele / Unsupervised-Learning-2023
This repository is dedicated to the lab activities of the course of Unsupervised Learning @UniTs
clustering density-estimation hierarchical-clustering isomap kernel-pca pca python scratch unsupervised-learning
Language:Jupyter Notebook
FabrizioMusacchio / machine_learning_for_image_denoising
This repository contains the Python code my blog post Image denoising techniques: A comparison of PCA, kernel PCA, autoencoder, and CNN. See post for more details and results.
autoencoder cnn convolutional-neural-networks image-denoising image-processing kernel-pca machine-learning pca
Language:Python
MehrabKalantary / News-Clustering
Applying NLP methods and kernel PCA on news dataset to build a clustering model
clustering dimensionality-reduction k-means-clustering kernel-pca kmeans-clustering nlp nlp-machine-learning
Language:Jupyter Notebook

kernel-pca

Albertsr / Anomaly-Detection

gionanide / Speech_Signal_Processing_and_Classification

Nikronic / Machine-Learning-Models

kaur-anupreet / Software-Defect-Prediction

lucko515 / dataset-dimensionality-reduction-python

bghojogh / Principal-Component-Analysis

mlesnoff / rchemo

kashefy / mi2notes

mlesnoff / rnirs

OleguerCanal / GPLVM

juyongjiang / VFedPCA-VFedAKPCA

MaxenceGiraud / BayesianPCA

namanUIUC / NonlinearComponentAnalysis

ratvec / ratvec

tejasnp163 / Dimensionality-Reduction-on-Wine-Dataset

bghojogh / Image-Structural-Component-Analysis

matteo-serafino / dimensionality-reduction-package

AAU-Dat / P5-Nonlinear-Dimensionality-Reduction

Arminkhayati / Machine_learning_lec

charumakhijani / machine-learning

algostatml / UNSUPERVISED-ML

EthanJamesLew / PSU_STAT672

hellpanderrr / ml_algorithms

Joycechidi / MachineLearning2

kyomangold / ETH-MachineLearning

longhongc / CMSC828C-hw6

BeataWereszczynska / UML_forged_banknotes

kisoo95 / DACON-Monthly-DACON-Credit-Card-Fraud-Deal-Detection-AI-Competition

mohammad95labbaf / UMAP_breast_cancer

shubhams821 / ML-Repository

vitthal-bhandari / High-Dimensional-Data-and-Gradient-Descent

williamagyapong / data-mining-projects

Abhishek-Nalawade / Kernel-PCA

alessimichele / Unsupervised-Learning-2023

FabrizioMusacchio / machine_learning_for_image_denoising

MehrabKalantary / News-Clustering