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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Decision Tree Classifier
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KNN Classifier
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Detailed explanation-1: -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-2: -Linear regression is used to predict the continuous dependent variable using a given set of independent variables. Logistic Regression is used to predict the categorical dependent variable using a given set of independent variables.
Detailed explanation-3: -Both linear and logistic regression are among the most popular models within data science, and open-source tools, like Python and R, make the computation for them quick and easy. Linear regression models are used to identify the relationship between a continuous dependent variable and one or more independent variables.
Detailed explanation-4: -1) Linear Regression Linear regression algorithm is used if the labels are continuous, like the number of flights daily from an airport, etc. The representation of linear regression is y = b*x + c.
Detailed explanation-5: -Linear Regression is an algorithm that belongs to supervised Machine Learning. It tries to apply relations that will predict the outcome of an event based on the independent variable data points. The relation is usually a straight line that best fits the different data points as close as possible.