A scala-based feature generation and modeling framework

Get Started »


Data science is filled with many mundane tasks that take up a majority of the data scientist’s time. Much of this revolves around formatting and transforming data to a form more amenable to learning or inference. Aloha attempts to alleviate this burden by providing a few things:

  • a DSL for feature specification based on familiar syntax
  • generic models that make use of this DSL
  • a pipeline for dataset generation using the same DSL

How does Aloha help?

Oftentimes machine learning libraries and models employ linear-algebraic data structure as their input type. For instance:

In Aloha, models are written generically, and different semantics implementations are provided to give meaning to the features extracted from the arbitrary input types on which the models operate.

Maven Setup


Back to top

Version: 3.3.1. Last Published: 2016-08-19.