latest
Install
Installing the released version with pip
Including optional torch dependencies for full functionality
Installing the released version with conda-forge
Python package dependencies
Hardware requirements
OS Requirements
Testing
Tutorials
Clustering
Multi-view KMeans
Assessing the Conditional Independence Views Requirement of Multi-view KMeans
Multi-view vs. Single-view KMeans
Multi-view Spectral Clustering
Assessing the Conditional Independence Views Requirement of Multi-view Spectral Clustering
Multi-view vs Single-view Spectral Clustering
Multi-view Spherical KMeans
Multi-view vs Single-view Spherical KMeans
Using the Multi-view Clustering Algorithm to Cluster Data with Multiple Views
Multi-view Vs Single-view Visualization and Clustering
Semi-Supervised
Co-Training 2-View Semi-Supervised Classification
Cotraining classification performance in simulated multiview scenarios
Co-Training 2-View Semi-Supervised Regression
Embedding
Generalized Canonical Correlation Analysis (GCCA)
GCCA vs PCA
Kernel CCA (KCCA)
Kernel CCA: ICD Method
Deep CCA (DCCA)
CCA Variants Comparison
Multiview Multidimensional Scaling (MVMDS)
MVMDS vs PCA
Omnibus Embedding for Multiview Data
SplitAE Embeddings on multiview MNIST data
Predicting views using SplitAE
Decomposition
Angle-based Joint and Individual Variation (AJIVE) Explained
Multiview Independent Component Analysis (ICA) Tutorial
Group ICA: a tutorial
Pipeline
Integrating mvlearn with scikit-learn
ViewTransformer
Mergers
Pipeline example: group-ICA
Plotting
Using quick_visualize() to quickly understand multi-view data
Plotting Across 2 Views
Test Dataset
Loading and Viewing the UCI Multiple Features Dataset
Multiview Data from Gaussian Mixtures
Multi-view Vs Single-view Visualization and Clustering
Reference
Clustering
Multiview Spectral Clustering
Co-Regularized Multiview Spectral Clustering
Multiview K Means
Multiview Spherical K Means
Semi-Supervised
Cotraining Classifier
Cotraining Regressor
Embedding
Generalized Canonical Correlation Analysis
Kernel Canonical Correlation Analysis
Deep Canonical Correlation Analysis
Omnibus Embedding
Multiview Multidimensional Scaling
Split Autoencoder
DCCA Utilities
Dimension Selection
Decomposition
Multiview ICA
Permutation ICA
Group ICA
Group PCA
Angle-Based Joint and Individual Variation Explained (AJIVE)
View Construction
Random Gaussian Projection
Random Subspace Method
Model Selection
Cross Validation
Compose
AverageMerger
ConcatMerger
SimpleSplitter
Preprocessing
ViewTransformer
Multiview Datasets
UCI multiple feature dataset (located here)
Data Simulator
Plotting
Quick Visualize
Crossviews Plot
Utility Functions
IO
Contributing to mvlearn
Submitting a bug report or a feature request
How to make a good bug report
Contributing Code
Pull Request Checklist
Guidelines
Coding Guidelines
Docstring Guidelines
API of mvlearn Objects
Estimators
Additional Functionality
Changelog
Version 0.4.0
mvlearn.compose
mvlearn.decomposition
mvlearn.model_selection
mvlearn.preprocessing
Version 0.3.0
Patch 0.2.1
Version 0.2.0
Version 0.1.0
License
Useful Links
mvlearn @ GitHub
mvlearn @ PyPI
Issue Tracker
mvlearn
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Reference
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Model Selection
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Model Selection
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Cross Validation
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