danaugrs/go-tsne

t-Distributed Stochastic Neighbor Embedding (t-SNE) in Go

42
/ 100
Emerging

This tool helps data scientists and analysts make sense of complex datasets by transforming high-dimensional data into a lower-dimensional visualization. You input your raw data, like a table of customer features or image pixels, or pre-calculated distances between data points. The output is a new set of coordinates for each data point that you can plot to reveal hidden patterns or clusters, making it easier to interpret intricate relationships.

225 stars. No commits in the last 6 months.

Use this if you need to visualize and understand the underlying structure of high-dimensional data, such as large sets of images, text documents, or biological samples, where traditional plotting methods fall short.

Not ideal if your primary goal is to build predictive models or if you need to retain the exact distances and global structure of your original data in the reduced dimensions.

data-visualization exploratory-data-analysis pattern-recognition machine-learning-research bioinformatics
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 16 / 25

How are scores calculated?

Stars

225

Forks

25

Language

Go

License

BSD-3-Clause

Category

go-ml-bindings

Last pushed

Dec 10, 2023

Commits (30d)

0

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