principal-components | Topic | Ecosyste.ms: Repos

Topic: "principal-components"

ganguli-lab/twpca

🕝 Time-warped principal components analysis (twPCA)

Language: Jupyter Notebook - Size: 43.4 MB - Last synced at: 6 months ago - Pushed at: about 4 years ago - Stars: 124 - Forks: 24

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.

Language: Jupyter Notebook - Size: 8.66 MB - Last synced at: about 2 months ago - Pushed at: over 4 years ago - Stars: 83 - Forks: 33

federicomarini/pcaExplorer

pcaExplorer - Interactive exploration of Principal Components of Samples and Genes in RNA-seq data

Language: R - Size: 60 MB - Last synced at: 4 days ago - Pushed at: 26 days ago - Stars: 56 - Forks: 17

jhoelzl/HRTF-Individualization

Head-related Transfer Function Customization Process through Slider using PCA and SH in Matlab

Language: MATLAB - Size: 19.3 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 49 - Forks: 14

benedekrozemberczki/NMFADMM

A sparsity aware implementation of "Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence" (ICASSP 2014).

Language: Python - Size: 7.13 MB - Last synced at: about 2 months ago - Pushed at: almost 3 years ago - Stars: 46 - Forks: 11

andylamp/federated_pca

Federated Principal Component Analysis Revisited!

Language: MATLAB - Size: 7.19 MB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 33 - Forks: 6

mkucz95/customer_segmentation

Unsupervised ML: Finding Customer Segments in General Population

Language: HTML - Size: 729 KB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 14 - Forks: 3

kennethleungty/Principal-Component-Regression

Principal Component Regression - Clearly Explained and Implemented

Language: Jupyter Notebook - Size: 1.04 MB - Last synced at: about 2 months ago - Pushed at: about 3 years ago - Stars: 12 - Forks: 5

nunofachada/amvidc

Data clustering algorithm based on agglomerative hierarchical clustering (AHC) which uses minimum volume increase (MVI) and minimum direction change (MDC) clustering criteria.

Language: Matlab - Size: 131 KB - Last synced at: about 2 months ago - Pushed at: over 9 years ago - Stars: 8 - Forks: 4

hkiang01/Applied-Machine-Learning

Applied Machine Learning

Language: Python - Size: 58.8 MB - Last synced at: about 2 years ago - Pushed at: almost 9 years ago - Stars: 7 - Forks: 4

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.

Language: HTML - Size: 286 MB - Last synced at: 12 months ago - Pushed at: about 7 years ago - Stars: 5 - Forks: 3

AdityaDutt/PCALinearityCheck

A demonstration of how to use PCA to see if data is linear or not

Language: Jupyter Notebook - Size: 1.68 MB - Last synced at: about 1 month ago - Pushed at: over 3 years ago - Stars: 3 - Forks: 0

LaxmiChaudhary/Classifying-silhouettes-of-vehicles

Unsupervised Learning (PCA) on Vehicle dataset

Language: Jupyter Notebook - Size: 4.68 MB - Last synced at: 8 months ago - Pushed at: over 5 years ago - Stars: 3 - Forks: 10

RenanWuicik7/Pontos_Principais_Html_Css

Anotações dos pontos principais dos Cursos de HTML e CSS iniciantes

Size: 7.81 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

saramille/Breast-cancer-Data-analysis

This repository is a series of notebooks that show analysis and modeling of the Breast Cancer data from Kaggle.

Language: Jupyter Notebook - Size: 466 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 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.

Language: R - Size: 4.19 MB - Last synced at: 23 days ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0

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.

Language: Jupyter Notebook - Size: 3.07 MB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 1

gianlucatruda/pca-vis

Real-time tool for exploring the relationships between PCA components and input features

Language: Python - Size: 6.48 MB - Last synced at: about 2 months ago - Pushed at: about 6 years ago - Stars: 1 - Forks: 0

quantfinlib/skpcp

python library for principal component pursuit

Language: Python - Size: 328 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

eiliaJafari/PCA-handwritten-digits

Figuring out which handwritten digits are most differentiated with PCA.

Language: Jupyter Notebook - Size: 916 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 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.

Language: R - Size: 5.81 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

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