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The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable's value is called the independent variable. K-NN is a non-parametric algorithm, which means it does not make any assumption on underlying data. It is also called a lazy learner algorithm because it does not learn from the training set immediately instead it stores the dataset and at the time of classification, it performs an action on the dataset. The Naive Bayes classification algorithm is a probabilistic classifier.