COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
Question
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Binary Logistic Regression


Multinomial Logistic Regression


Ordinal Logistic Regression


Linear Regression

Detailed explanation1: Logistic regression is an approach for demonstrating the relationship between a binary dependent variable, and several explanatory variables. With the dependent variable being binary, it can only take on two values, which in this case is ”Spam”, or ”No Spam”.
Detailed explanation2: Logistic regression is one of the most likely and appropriate algorithm used for classification of datasets. In case of classifying a dataset named as spam base the logistic regression is the most versatile decision based approach for detecting spam emails out of a dataset.
Detailed explanation3: With Bayes’ Rule, we want to find the probability an email is spam, given it contains certain words. We do this by finding the probability that each word in the email is spam, and then multiply these probabilities together to get the overall email spam metric to be used in classification.
Detailed explanation4: The methodology is used for the process of email spam filtering based on Naıve Bayes algorithm. 3.1. Naıve Bayes classifier The Naıve Bayes algorithm is a simple probabilistic classifier that calculates a set of probabilities by counting the frequency and combination of values in a given dataset [4].