Day 14

Today I continued testing different parameters for the MLP classifier. While I ran tests, I finished documenting the classifiers that I am testing. I also wrote an introduction to my descriptions of the preprocessing methods, finished citations for the descriptions, and wrote a summary of my preprocessing experiment in an article being written in Overleaf about the machine learning pipeline. Although I am not yet ready to test the next classifier, RandomForest, I began writing code to test for the optimal preprocessing methods and parameters to use with it. Throughout the day, I collected data on the metrics of different combinations of parameters for MLP. I looked through this data and ran a larger number of trials on the most promising parameters, but it still appears that the default parameters are the most accurate, even though the overall accuracy resulting from the default parameters averages at about seventy percent, which is not very good compared to the other two classifiers I have tested so far. Tomorrow I plan to run coarse and fine grid searches to try to find more effective parameters for MLP.

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