Method
Naive Bayes
Naive Bayes classifiers are a family of simple probabilistic classifiers based on applying Bayes' theorem with strong (naive) independence assumptions between the features.
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Decision Tree:
A decision tree is a tree-like structure in which each internal node represents a "test" on an attribute, each branch represents the outcome of the test and each leaf node represents a class label. The paths from root to leaf represents classification rules.
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5-Nearest Neighbor:
The object will be assigned to the class most common among its 5 nearest neighbors.
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Multilayer Perceptron:
A multilayer perceptron (MLP) is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate outputs.
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Four classifiers in “weka” was used to train and test the dataset generated from the previous steps : Naive Bayes, Decision tree, 5-nearest neighbor and multilayer perceptron. The results are shown in the table and figure below
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Results
Dataset
The dataset in .json format is provided on Yelp’s website.
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