KNN and SVM Classifiers | KNN Classifiers | SVM Classifiers | aiensured.com

KNN and SVM Classifiers
In several practical analytics scenarios we need to perform machine learning with specific output variable. In the case of examples like determining if a person has to be given a credit card or not the output, variable is discrete and the method is classification.
Most elegant approach in classification is that of lazy nearest neighbour classification method or SVM method
The lazy knn method tries to estimate class by looking at the majority class of the rows nearest to the current row
in SVM support vector machine we try to form a plan separating the class with maximal distance between the two classes..We also include points from either side called support vectors to be included in the model..
The technique used to determine which variable will be used to split the tree at any point is detemined by entropy..
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