principal-components

There are 0 repository under principal-components topic.

ganguli-lab / twpca
🕝 Time-warped principal components analysis (twPCA)
dimensionality-reduction neuroscience principal-components time-warp
Language:Jupyter Notebook 124
syamkakarla98 / Dimensionality-reduction-and-classification-on-Hyperspectral-Images-Using-Python
In this repository, You can find the files which implement dimensionality reduction on the hyperspectral image(Indian Pines) with classification.
python-3 hyperspectral-image-classification matplotlib numpy pandas indian-pines dimensionality-reduction pca classification principal-components hacktoberfest2020 hacktoberfest
Language:Jupyter Notebook 83
jhoelzl / HRTF-Individualization
Head-related Transfer Function Customization Process through Slider using PCA and SH in Matlab
hrtf-individualization hrtf matlab principal-components spherical-harmonics pca headphone database adjustement adjustments acoustic
Language:MATLAB 61
federicomarini / pcaExplorer
pcaExplorer - Interactive exploration of Principal Components of Samples and Genes in RNA-seq data
principal-components rna-seq-data rna-seq-analysis r shiny transcriptome reproducible-research user-friendly bioconductor
Language:R 54
NMFADMM
benedekrozemberczki / NMFADMM
A sparsity aware implementation of "Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence" (ICASSP 2014).
nmf factorization matrix-factorization lda pca principal-components principal-component-analysis embedding word-embedding word2vec deepwalk node2vec admm optimization unsupervised-learning unsupervised-machine-learning feature-extraction sparse-matrix beta-divergence topic-modeling
Language:Python 43
andylamp / federated_pca
Federated Principal Component Analysis Revisited!
pca streaming federated-learning decentralized streaming-algorithms online-learning subspace-tracking differential-privacy perturbation-mask principal-components federated-pca dimensionality-reduction
Language:MATLAB 36
mkucz95 / customer_segmentation
Unsupervised ML: Finding Customer Segments in General Population
unsupervised-learning customer-segmentation udacity-data-science-nanodegree principal-components clustering
Language:HTML 16
kennethleungty / Principal-Component-Regression
Principal Component Regression - Clearly Explained and Implemented
pca principal-component-analysis principal-component-regression pcr regression principal-components principal-component-analysis-pca regression-analysis linear-regression python
Language:Jupyter Notebook 11
hkiang01 / Applied-Machine-Learning
Applied Machine Learning
machine-learning-algorithms machine-learning r python naive-bayes svm iris-dataset caret klar principal-component-analysis principal-components em-algorithm nips linear-regression ridge-regression regularization lasso-regression elasticnet convolu tensorflow
Language:Python 7
nunofachada / amvidc
Data clustering algorithm based on agglomerative hierarchical clustering (AHC) which uses minimum volume increase (MVI) and minimum direction change (MDC) clustering criteria.
clustering-algorithm clustering-criteria clustering matlab fscore data-clustering-algorithm cluster-analysis minimum-volume-increase minimum-direction-change pddp principal-components algorithm volume convex-hull convexhull matlab-toolbox
Language:MATLAB 7
charlesdavid / JED
JED is a program for performing Essential Dynamics of protein trajectories written in Java. JED is a powerful tool for examining the dynamics of proteins from trajectories derived from MD or Geometric simulations. Currently, there are two types of PCA: distance-pair and Cartesian, and three models: COV, CORR, and PCORR.
pca-analysis subspace-identification covariance-matrix correlation-matrices essentialmode principal-components dynamical-modeling correlation-measures pymol free-energy kernel-density-estimation eigen-vector-decomposition
Language:HTML 5
AdityaDutt / PCALinearityCheck
A demonstration of how to use PCA to see if data is linear or not
pca principal-component-analysis linear non-linear hyperspher python principal-components
Language:Jupyter Notebook 3
LaxmiChaudhary / Classifying-silhouettes-of-vehicles
Unsupervised Learning (PCA) on Vehicle dataset
pca logistic-regression support-vector-machine naive-bayes-classification unsupervised-machine-learning machine-learning supervised-machine-learning principal-component-analysis principal-components machine-learning-algorithms machinelearning unsupervised-learning-algorithms unsupervised supervised-learning supervised-learning-algorithms naive-bayes-classifier naive-bayes-algorithm
Language:Jupyter Notebook 3
atrishi / PCA-Clustering-K-means-Hierarchical-Poverty-Analysis
Analysis of global poverty using PCA to identify important parameters and then clustering via both K-means and Hierarchical clustering techniques.
poverty developmental-economics economics economic-data clustering k-means-clustering k-means-implementation-in-python k-means hierarchical-clustering hierarchical-models clustering-methods clustering-evaluation pca pca-analysis principal-component-analysis principal-components
Language:Jupyter Notebook 2
michstg / DiabetesClassification-DecisionTree-PCA-TuningParameter
Classification-Diabetic-Machine Learning-Algorithm-Decision Tree-Improve by-Principle Component Analysis
data-visualization decision-tree-classifier diabetes-dateset-analysis diabetes-prediction exploratory-data-analysis machine-learning machine-learning-algorithms pca-analysis principal-component-analysis principal-components python statistical-analysis tuning-parameters
Language:Jupyter Notebook 2
evrial / PCA-dimensionality-reduction
Minimal PCA library based on numpy and examples of practical dimensionality reduction use of the principal components in ETF market analysis.
dimension-reduction dimensionality eigenvectors pca principal-components risk
Language:Jupyter Notebook 1
gianlucatruda / pca-vis
Real-time tool for exploring the relationships between PCA components and input features
data-science dimensionality-reduction interactive matplotlib-pyplot pca principal-component-analysis principal-components pygame sklearn
Language:Python 1
gouravaich / faces-recognition-pca
Faces recognition example using eigenfaces and SVMs
machine-learning udacity-nanodegree pca face-recognition eigenfaces svm svm-classifier classification-report confusion-matrix principal-component-analysis principal-components explained-variance f1-score
Language:Jupyter Notebook 1
RenanWuicik7 / Pontos_Principais_Html_Css
Anotações dos pontos principais dos Cursos de HTML e CSS iniciantes
anotation notes principal-components
1
saramille / Breast-cancer-Data-analysis
This repository is a series of notebooks that show analysis and modeling of the Breast Cancer data from Kaggle.
dimensionality-reduction covariance-matrices heatmap pca dimension-reduction principal-component-analysis principal-components covariance-matrix standardization normalization knearest-neighbor-classifier knn svm-classifier svm-model logistic-regression cross-validation sensitvity recall
Language:Jupyter Notebook 1
xinghuq / DA
DA incorporates the commonly used linear and non-linear, local and global supervised learning approaches (discriminant analysis). These discriminant analyses can be used to do ecological and evolutionary inference. We show the examples of demographic history inference, species identification, and population structure inference in the vignettes using the supervised discriminant analysis.
discriminant-analysis kernel-principle-components dapc kernel-local population-structure-inference ecological kernel principal-components
Language:R 1
aritra90 / COGG
This repository contains instructions to run the method, COGG or Correlation Optimization of Genetics and Geodemographics.
genetics principal-components correlation-optimization statistics
Language:MATLAB 0
fracomp / Market-Research-and-forecasting
principal-component-analysis principal-components factor-analysis unsupervised-learning arima arima-model acf pacf time-series
0
isammitr / identifyCustomerSegments
Unsupervised Learning: Identify Customer Segments  - Principal Component Analysis and Clustering
demographics-data principal-components unsupervised-learning
Language:Jupyter Notebook 0
different_processings_for_ML
Jean-Lcs / different_processings_for_ML
In this project, we use differents methods to transform our dataset (usually dimension modification) before making prediction thanks to machine learning and regressions.
dimensional-analysis dimensionality-reduction dimensionality-reduction-technique ols-regression pca pca-analysis principal-component-analysis principal-component-analysis-pca principal-components regularisation regularisation-methods ridge ridge-regression variable-selection variables
Language:Jupyter Notebook 0
k41m4n / eigenfaces
This repository provides code in R for the computer vision problem of human face recognition.
eigenfaces principal-component-analysis svd face-images train-face face-recognition eigenvectors test-face principal-components eigenvalues computer-vision weights
Language:R 0
KAR-NG / Human-Resource-Data-Mining
5 analytical tasks have been completed using VAT validated gower-PAM clustering, Correspondence Analysis (CA), Asym-Biplot, Multiple Correspondence Analysis (MCA), Chi-Squared test, Regression, and predictive classification models with KNN, SVM, and Random Forest.
r classification clustering data datamining machine-learning principal-components regression
Language:R 0
monti-nicolas / unsupervised-learning-clustering
Using principal component and clustering analysis on a customer segmentation case.
data-science unsupervised-learning machine-learning data-exploration principal-components clustering feature-engineering udacity-nanodegree
Language:Jupyter Notebook 0
paulinealvarado / stanford-stat-learning
Supervised learning and unsupervised in R, with a focus on regression and classification methods.
logistic-regression linear-discriminant-analysis quadratic-discriminant-analysis cross-validation bootstrap model-selection regularization-methods ridge lasso splines generalized-additive-models tree-based-methods random-forests boosting support-vector-machnes principal-components clustering knn
Language:R 0
ricardoariasalazar / EM-for-Document-Clustering
Classifying abstracts of different papers using unsupervised learning algorithms like soft and hard Expectation Maximization.
document-classification expectation-maximization machine-learning principal-components unsupervised-learning
Language:Jupyter Notebook 0
alex-mathew / PCT-Based-Image-Denoising
Project under the supervision of Prof. B. Krishna Mohan, Satellite Image Processing Lab, CSRE, IITB to denoise a 4 band satellite image using a pipeline of PCT, Removal of PC corresponding to lowest Eigen Value and Inverse PCT
satellite-imagery image-processing principal-components
Language:Python
DSCPoltekpos / Py-PCA-Calory
Method Principal Component Analysis
pca principal-component-analysis principal-components scikitlearn-machine-learning machine-learning machine-learning-algorithms
Language:Python
eddyherrera / Estad-stica-Aplicada-Multivariada
Estadística Aplicada
regression-models cluster-analysis componentes principal-components
eiliaJafari / PCA-handwritten-digits
Figuring out which handwritten digits are most differentiated with PCA.
data-analysis digit-recognition handwritten-digit-recognition handwritten-digits pca principal-component-analysis principal-components
Language:Jupyter Notebook
nakshatra108 / Principal-Component-Analysis
Used Principal Component Analysis on Iris Dataset and reduced it from 4-features to 3-features and captured 93% of variance
pca principal-component-analysis principal-component-analysis-pca principal-components
Language:Jupyter Notebook
Xisurthros / R_Guide
Running through some R refresher
r hierarchical-clustering principal-components regression
Language:R

principal-components

ganguli-lab / twpca

syamkakarla98 / Dimensionality-reduction-and-classification-on-Hyperspectral-Images-Using-Python

jhoelzl / HRTF-Individualization

federicomarini / pcaExplorer

benedekrozemberczki / NMFADMM

andylamp / federated_pca

mkucz95 / customer_segmentation

kennethleungty / Principal-Component-Regression

hkiang01 / Applied-Machine-Learning

nunofachada / amvidc

charlesdavid / JED

AdityaDutt / PCALinearityCheck

LaxmiChaudhary / Classifying-silhouettes-of-vehicles

atrishi / PCA-Clustering-K-means-Hierarchical-Poverty-Analysis

michstg / DiabetesClassification-DecisionTree-PCA-TuningParameter

evrial / PCA-dimensionality-reduction

gianlucatruda / pca-vis

gouravaich / faces-recognition-pca

RenanWuicik7 / Pontos_Principais_Html_Css

saramille / Breast-cancer-Data-analysis

xinghuq / DA

aritra90 / COGG

fracomp / Market-Research-and-forecasting

isammitr / identifyCustomerSegments

Jean-Lcs / different_processings_for_ML

k41m4n / eigenfaces

KAR-NG / Human-Resource-Data-Mining

monti-nicolas / unsupervised-learning-clustering

paulinealvarado / stanford-stat-learning

ricardoariasalazar / EM-for-Document-Clustering

alex-mathew / PCT-Based-Image-Denoising

DSCPoltekpos / Py-PCA-Calory

eddyherrera / Estad-stica-Aplicada-Multivariada

eiliaJafari / PCA-handwritten-digits

nakshatra108 / Principal-Component-Analysis

Xisurthros / R_Guide