ivis: structure preserving dimensionality reductionΒΆ

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ivis is a machine learning algorithm for reducing dimensionality of very large datasets. ivis preserves global data structures in a low-dimensional space, adds new data points to existing embeddings using a parametric mapping function, and scales linearly to millions of observations. The algorithm is described in detail in Structure-preserving visualisation of high dimensional single-cell datasets.

The latest development version is on github.

API Reference: