Try it online
Rapaio is a rich collection of data mining, statistics and machine learning tools written completely in Java. Documentation for this library is hosted as github pages. Most of the documentation is written as Jupyter notebooks and hosted at rapaio-notebooks github repository. The notebooks repository can also be spin up through binder.
The complete list of features is presented here. An incomplete list of implemented algorithms and features includes: core statistical tools, common distributions and hypothesis testing, Naive Bayes, Binary Logistic Regression, Decision Trees (regression and classification), Random Forests (regression and classification), AdaBoost, Gradient Boosting Trees (regression and classification), BinarySMO SVM, Relevant Vector Machines (regression), Linear and Ridge Regression, PCA and KMeans. Additionaly there is a fair share of graphical tools and linear algebra stuff. And the list is growing periodically.
Last published release on maven central is 3.0.0
<dependency> <groupId>io.github.padreati</groupId> <artifactId>rapaio</artifactId> <version>3.0.0</version> </dependency>
The best way for exploration is through jupyter / jupyter-lab notebooks. This is excellent for experimenting with interactive notebooks or to document the ideas you are working on. You have to install jupyter / jupyter-lab and IJava kernel. For more information you can follow the instruction from IJava. The following notation is specific to IJava kernel jupyter notation.