Download JAR files tagged by assumption with all dependencies

It is a library to compress and uncompress arrays of integers very fast. The assumption is that most (but not all) values in your array use less than 32 bits.

A tiny server starter for easy and minimal microservice handling. This is based on the assumption that the microservice does not use the admin HTTP server for anything but kubernetes status management. Dependencies are kept at a minimum, but should cover the basic needs of any microservice.

Stochastice Performance Logic is a formalism for capturing performance assumptions. It is, for example, possible to capture assumption that newer version of a function bar is faster than the previous version or that library foobar is faster than library barfoo when rendering antialiased text. The purpose of this framework is to allow evaluation of SPL formulas inside Java applications.

Lazy Bayesian Rules Classifier. The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. Lazy Bayesian Rules selectively relaxes the independence assumption, achieving lower error rates over a range of learning tasks. LBR defers processing to classification time, making it a highly efficient and accurate classification algorithm when small numbers of objects are to be classified. For more information, see: Zijian Zheng, G. Webb (2000). Lazy Learning of Bayesian Rules. Machine Learning. 4(1):53-84.