Streaming Histograms
A Clojure/Java library for streaming, one-pass histograms that approximate data distributions for learning, visualization, and analysis.
What is Streaming Histograms?
Histogram is a Clojure/Java library that implements streaming, one-pass histograms for approximating data distributions. It allows developers to build, merge, and query histograms efficiently in memory-constrained environments, supporting both numeric and categorical target tracking. The library is designed for real-time data analysis and scalable machine learning pipelines.
Data engineers and scientists working with large-scale streaming data, particularly those implementing distributed machine learning algorithms or needing efficient data summarization for visualization and analysis in Clojure or Java ecosystems.
Developers choose Histogram for its streaming capabilities, merge-friendly design enabling parallel processing, and configurable performance optimizations, offering a practical balance between accuracy and resource usage for real-time data approximation.
Overview
Streaming Histograms for Clojure/Java
Use Cases
Best For
- Building distributed decision tree algorithms that require efficient data summarization
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