Classification: Classification is a machine learning task of predicting the value of a categorical variable(target or class). This is done by building a modal based on one or more numerical and categorical variables( predictors, attributes or features). It is considered an instance of supervised learning.
Classification is the problem of identifying to which of a set of categories a new observation belongs, on the basis of training data containing observations. Classification models include linear models like Logistic Regression, SVM, and nonlinear ones like K-NN, Kernel SVM, and Random Forests.
Now, we will learn how to implement the following Machine Learning Classification models:
K-Nearest Neighbors (K-NN)
Support Vector Machine (SVM)
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