Sentence examples for machine learning ensemble from inspiring English sources

Comparison of the FPGA implementation of REC architecture with standard WEKA software implementation suggests that proposed hardware architecture offers substantial speed-ups for all types of considered machine learning ensemble classifiers, ranging from 102 to 105 times.

Random Forest can be viewed as a machine learning ensemble algorithm and was first proposed by Breiman [ 11].

A machine learning ensemble can be simply viewed as a combination of a number of models that have been trained independently from the available data of a given problem and then work collectively in order to produce better solutions.

As is typically the case in machine learning, ensemble methods performed well (this would also have been true in CAFA), although investigator-based choices also appear to have been critical, since the class of purely automated methods performed particularly badly.

In the future, we plan to use machine learning ensemble (or bagging) techniques to integrate different predictors evaluated in this research and some other predictors such as IUP [ 12] together to improve disorder prediction.

This research work adduces new hybrid machine learning ensembles for improving the performance of a computer aided diagnosis system integrated with multimethod assessment process and statistical process control, used for the spine diagnosis based on noninvasive panoramic radiographs.

Due to its large dimensionality, it is implemented using machine learning tool, ensemble classifier [16] which consists of many base learners such as FLD [29].

This approach is an instance of the machine learning method of ensemble learning, and requires sufficient differences between the systems combined [21].

The architecture is based on a structure which unifies several concepts from machine learning such as ensemble methods, local learning, meta learning and concept drift handling.

In the future, we will further improve the classification performance by investigating other machine learning algorithms or ensembles of classifiers.

The ensemble machine learning paradigm has been established to tackle this challenge.