APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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The algorithm creates a line or a hyperplane which separates the data into classes and also suitable for classification and regression
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K-means clustering
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Support vector machine
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Bayesian inference
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perceptron
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Explanation:
Detailed explanation-1: -Support Vector Machine is the supervised machine learning algorithm, that is used in both classification and regression of models. The idea behind it is simple to just find a plane or a boundary that separates the data between two classes.
Detailed explanation-2: -Linear SVM: Hence, the SVM algorithm helps to find the best line or decision boundary; this best boundary or region is called as a hyperplane.
Detailed explanation-3: -Margin: it is the distance between the hyperplane and the observations closest to the hyperplane (support vectors). In SVM large margin is considered a good margin.
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