Sentence examples for machine learning packages from inspiring English sources

A few machine learning packages implement semi-automated model hyper-parameter selection.

Some of them are implemented in various machine learning packages, but many are not.

Table 2 provides an overview of four of the more comprehensive machine learning packages that run on Hadoop.

AZOrange complements already available machine learning packages by interfacing and customizing several state-of-the-art machine learning algorithms.

Despite the diversity of available machine learning packages, there is no package fulfilling all of the requirements on an Open Source state-of-the-art QSAR modeling platform.

The R package caret provides a common interface to the most popular machine learning packages that exist in R, and, as such, camb invokes caret to set up cross-validation frameworks and train machine learning models.

Calling the algorithms was done using the Scikit-learn machine learning package [79, 80].

This paper describes the implementation of the Open Source machine learning package AZOrange.

We use the MALLET machine learning package (McCallum [2002]) which provides an open source implementation of LDA.

We employed information gain attribute evaluator, relief attribute evaluator, and correlation-based feature selection (CFS) from Weka machine learning package [62] for the gene selection.

Classification was done using Support Vector Machine classifiers as implemented in the WEKA machine learning package [ 27].