COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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logistic regression
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linear regression
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linear predictions
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label predictions
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Detailed explanation-1: -Linear regression is utilized for regression tasks, while logistic regression helps accomplish classification tasks. Supervised machine learning is a widely used machine learning technique that predicts future outcomes or events. It uses labeled datasets to learn and generate accurate predictions.
Detailed explanation-2: -Logistic regression is a statistical analysis method to predict a binary outcome, such as yes or no, based on prior observations of a data set. A logistic regression model predicts a dependent data variable by analyzing the relationship between one or more existing independent variables.
Detailed explanation-3: -Logistic Regression is one of the basic and popular algorithms to solve a classification problem. It is named ‘Logistic Regression’ because its underlying technique is quite the same as Linear Regression. The term “Logistic” is taken from the Logit function that is used in this method of classification.
Detailed explanation-4: -The logit in logistic regression is a special case of a link function in a generalized linear model: it is the canonical link function for the Bernoulli distribution. The logit function is the negative of the derivative of the binary entropy function.