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0.5.0

Using mvlearn

  • Overview of mvlearn
  • Install
    • pip installation instructions
    • conda installation instructions
      • Including optional dependencies for full functionality
    • Python package dependencies
    • Hardware requirements
    • OS Requirements
    • Testing
  • Examples Gallery
    • Examples on cluster
      • Multiview Coregularized Spectral Clustering Comparison
      • Multiview Spherical KMeans Tutorial
      • Multiview KMeans Tutorial
      • Multiview vs. Singleview Spectral Clustering of UCI Multiview Digits
      • Multiview vs. Singleview KMeans
      • Multiview Spectral Clustering Tutorial
      • Multiview vs. Singleview Spectral Clustering
      • Conditional Independence of Views on Multiview Spectral Clustering
      • Conditional Independence of Views on Multiview KMeans Clustering
    • Examples on compose
      • Constructing multiple views to classify singleview data
      • Integrating mvlearn with scikit-learn
    • Examples on datasets
      • Loading and Viewing the UCI Multiple Features Dataset
      • Generating Multiview Data from Gaussian Mixtures
      • An mvlearn case study: the Nutrimouse dataset
    • Examples on decomposition
      • ICA: a tutorial
      • Multiview Independent Component Analysis (ICA) Comparison
      • Angle-based Joint and Individual Variation Explained (AJIVE)
    • Examples on embed
      • Generalized Canonical Correlation Analysis (GCCA) Tutorial
      • CCA Tutorial
      • Deep CCA (DCCA) Tutorial
      • Partial Gram-Schmidt Orthogonalization (PGSO) for KMCCA
      • Multidimensional Scaling (MVMDS) Tutorial
      • Comparing CCA Variants
      • Kernel MCCA (KMCCA) Tutorial
    • Examples on plotting
      • Quickly Visualizing Multiview Data
      • Plotting Multiview Data with a Cross-view Plot
    • Examples on semi_supervised
      • 2-View Semi-Supervised Regression
      • 2-View Semi-Supervised Classification
  • Reference
    • Embedding
      • Canonical Correlation Analysis (CCA)
      • Multiview Canonical Correlation Analysis (MCCA)
      • Kernel MCCA
      • Generalized Canonical Correlation Analysis (GCCA)
      • Deep Canonical Correlation Analysis (DCCA)
      • Multiview Multidimensional Scaling
      • Split Autoencoder
      • DCCA Utilities
      • Dimension Selection
    • Decomposition
      • Multiview ICA
      • Group ICA
      • Group PCA
      • Angle-Based Joint and Individual Variation Explained (AJIVE)
    • Clustering
      • Multiview Spectral Clustering
      • Co-Regularized Multiview Spectral Clustering
      • Multiview K Means
      • Multiview Spherical K Means
    • Semi-Supervised
      • Cotraining Classifier
      • Cotraining Regressor
    • Model Selection
      • Cross Validation
      • Train-Test Split
    • Compose
      • AverageMerger
      • ConcatMerger
      • RandomGaussianProjection
      • RandomSubspaceMethod
      • SimpleSplitter
      • ViewClassifier
      • ViewTransformer
    • Multiview Datasets
      • UCI multiple feature dataset
      • Nutrimouse dataset
      • Data Simulator
      • Factor Model
    • Plotting
      • Quick Visualize
      • Crossviews Plot
    • Utility Functions
      • IO

Developer Information

  • 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 0.5.0
    • Version 0.4.1
    • Version 0.4.0
      • mvlearn.compose
      • mvlearn.construct
      • mvlearn.decomposition
      • mvlearn.embed
      • mvlearn.model_selection
      • mvlearn.utils
    • 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
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