Classification Performance Measures
How to measure classification performance
Multiple methods exist to measure the performance of a classification algorithm and classify a data set into two classes, positive and classified.
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Multiple methods exist to measure the performance of a classification algorithm and classify a data set into two classes, positive and classified.
KNN classifier is a nonparametric lazy classifier. In nonparametric classification the algorithm does not assume any specific distribution for the data sets.
Support Vector Machine is a binary parametric classifier that classifies items by creating a hyperplane between classes.
A rule-based classifier uses a set of rules to classify items in a data set. The rules are formalised in the form of IF-THEN clause.
Decision Tree is a classification model which recursively partitions the data space into two parts. The split can be considered as a hyperplane parallel to one axis of the data space.