This past week I completed another Edx Lab (4b). In the lab, I trained and evaluated a classification model. Classification is one of the fundamental machine learning methods used in data science. Classification models enable you to predict classes or categories of a label value. Classification algorithms can be two-class methods, where there are two possible categories, or multi-class methods. Like regression, classification is a supervised machine learning technique, wherein models are trained from labeled cases.
This lab is important, because we will perform classification on our ABB data.
I also spent some time figuring out what another classification experiment was doing in our SERESL Azure space. The student was performing multiple two-class bayes point algorithm on different eye-tracking categorical data from each task performed in the study. He also ran a two-class decision forest algorithm on task 2 in multiple different ways.
This lab is important, because we will perform classification on our ABB data.
I also spent some time figuring out what another classification experiment was doing in our SERESL Azure space. The student was performing multiple two-class bayes point algorithm on different eye-tracking categorical data from each task performed in the study. He also ran a two-class decision forest algorithm on task 2 in multiple different ways.
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