Abstract
Machine learning entails making changes to the systems that carry out
artificial intelligence (AI)-related tasks. It displays the many ML kinds and
applications. It also explains the fundamental ideas behind feature selection methods
and how they can be applied to a variety of machine learning (ML) techniques,
including artificial neural networks (ANN), Naive Bayes classifiers (probabilistic
classifiers), support vector machines (SVM), K Nearest Neighbour (KNN), and
decision trees, also known as the greedy algorithm.
Keywords: Algorithms, Artifical intelligence, Classification, Learning methods, Machine learning, Svm.
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