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We implemented the three methods in java using Weka machine learning workbench [38].
Decision trees were generated using the j48 implementation of the C4.5 decision tree algorithm from the Weka machine learning workbench [33].
We used the Weka machine learning workbench [38] for implementing the spectrum, and LA kernels (RBF kernel is already implemented in Weka).
We used the ADTree algorithm included in the MALIBU machine learning workbench [ 42].
19 classifier implemented in WEKA, 24 a widely used machine learning workbench in bioinformatics implemented in Java. Figure 1 summarizes the PSO for undersampling technique.
In this study, we used an R interface in Waikato Environment for Knowledge Analysis (WEKA) 3.6 software, a popular machine learning workbench developed by researchers in University of Waikatoi [ 46, 47].
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The popular machine-learning workbench Weka is included to provide PLS modeling, as well as an in-house implementation.
The WEKA workbench [ 48] is a data mining environment that includes several machine learning algorithms including RF.
What is machine learning?
The Machine Learning Workbench is a desktop client for Windows and Mac (and yes, in this brave new world, Mac apps from Microsoft really aren't a big deal anymore) that, in Microsoft's words, is meant to be the "control panel for your development lifecycle and a great way to get started using machine learning".
machine learning.
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