Different kernels in SVM

 There are four types of kernels in SVM.

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Decision Tree algorithm

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A decision tree is a supervised machine learning algorithm mainly used for Regression and Classification. It breaks down a data set into smaller and smaller subsets while at the same time an associated decision tree is incrementally developed. The final result is a tree with decision nodes and leaf nodes. A decision tree can handle both categorical and numerical data.  
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Real life example for linear regression: drug dosage and blood pressure of patients

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