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openTSNE: A Modular Python Library for t-SNE Dimensionality Reduction and Embedding
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DOI：10.18637/jss.v109.i03.png)
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Abstract
En 中文
One of the most popular techniques for visualizing large, high-dimensional data sets is t -distributed stochastic neighbor embedding (t -SNE). Recently, several extensions have been proposed to address scalability issues and the quality of the resulting visualizations. We introduce openTSNE , a modular Python library that implements the core t -SNE algorithm and its many extensions. The library is faster than existing implementations and can compute projections of data sets containing millions of data points in minutes.
Keywords:
t-SNE
embedding
visualization
dimensionality reduction
Python
Journal
IF:
8.1
Papers:
622
Citations:
4.6W