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The Classification algorithm is a Supervised Learning technique that is used to identify the category of new observations on the basis of training data. In Classification, a program learns from the given dataset or observations and then classifies new observations into a number of classes or groups. In this video, you will learn about comparisons between some of the most common and popular classification algorithms and see the factors that lead to comparison. You will also, see how to evaluate each and every algorithm’s performance based on a case study and finally summarize everything. So, if you feel the need to dig deeper into the Real-time application of the classification algorithms, sit tight as we bring to you all the information you need right on your screens.

00:00:00 Introduction
00:03:15 Parameters For Comparison
00:09:01 Promotion Problem Statement
00:16:07 Preprocessing Data
00:33:15 Logistic Regression
00:49:39 Support Vector Machine
01:01:10 K Nearest Neighbours
01:06:47 Naive Bayes
01:13:05 Decision Tree
01:20:23 Random Forest

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