Sentence examples for machine learning package from inspiring English sources

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

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

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.

The implementation of the algorithm was adapted from the WEKA machine learning package [ 52].

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

For biomarker discrimination tasks using a support vector machine (SVM) classifier, we used the Spider machine learning package, version 1.71 [ 25].

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.

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.

However, it would be helpful if students know Python already for they will use existing machine learning packages in Python.