Читать книгу Bioinformatics and Medical Applications - Группа авторов - Страница 18

Machine learning and information gathering utilizes ensembles on one or more learning algorithms to get different arrangement of classifiers with the ability to improve performance. Experimental studies have time and again proven that it is unusual to get one classifier which will perform the best on the general problem domain. Hence, ensemble of classifiers is often produced using any of the subsequent methods.

 • Splitting the data and using various chunks of the training data for single machine learning algorithm.

 • Training one learning algorithm using multiple training parameters.

 • Using multiple learning algorithms.

Key ideas such as the data setup, data classification, data mining models, and techniques are described below.