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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Multiple Linear Regression
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Polynomial Regression
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Detailed explanation-1: -Multiple regression is a machine learning algorithm to predict a dependent variable with two or more predictors.
Detailed explanation-2: -Linear regression Linear Regression is an ML algorithm used for supervised learning. Linear regression performs the task to predict a dependent variable(target) based on the given independent variable(s).
Detailed explanation-3: -Multinomial logistic regression is a simple extension of binary logistic regression that allows for more than two categories of the dependent or outcome variable. Like binary logistic regression, multinomial logistic regression uses maximum likelihood estimation to evaluate the probability of categorical membership.
Detailed explanation-4: -Support Vector Machine (SVM) Similar to decision tree and random forest, support vector machine can be used in both classification and regression, SVC (support vector classifier) is for classification problem.
Detailed explanation-5: -Multiple regression model is one that attempts to predict a dependent variable which is based on the value of two or more independent variables.