In this chapter, I explained the the data being used for experimentation including its format\cite{weka}, sources\cite{promiseData}, and its attributes. I also covered the experimental methods. The layout of the experiments, and the evaluation criteria were detailed. The results are displayed using quartile charts, and will include the Mann-Whitney-Wilcoxin U-Test ranks. Finally, the different experiments performed were detailed. These include:
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\item A comparison of locality based and non-locality based classifiers. This will show the effects of locality during classification.
\item A comparison of the application of a relevancy filter versus not applying the filter. This will show the effects of locality during training.
\item A comparison of various clustering algorithms versus no pre-processing. This will show the effects of locality during the instance selection process. I will demonstrate this process by using the clustering algorithm to select the local training data for each testing instance. I will then retrain the classifier with this new local training data.
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Many results were observed in the process of running the above experiments, and the next chapter will present these results.
