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iDA

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Define embedding space for data with clustered architecture

v0.99.6 · MIT + file LICENSE
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Description

iterative discriminant analysis (iDA) is a dimensionality reduction technique which identifies latent clustering and performs linear transformations to maximally embed this clustering. iDA can take both numeric matrices as well as SummarizedExperiment and SingleCellExperiment objects. The output from iDA is a vector of estimated latent clustering assignments as well as linear discriminants (LDs) as the embedded reduction.

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Topics

Software
Software › StatisticalMethod › DimensionReduction
Software › StatisticalMethod › Clustering

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