APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Linear
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non linear
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Either A or B
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None of the above
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Detailed explanation-1: -Perceptron is a linear Machine Learning algorithm used for supervised learning for various binary classifiers. This algorithm enables neurons to learn elements and processes them one by one during preparation.
Detailed explanation-2: -Yes a perceptron (one fully connected unit) can be used for regression. It will just be a linear regressor. If you use no activation function you get a regressor and if you put a sigmoid activation you get a classifier.
Detailed explanation-3: -It is called a linear classifier because its decision boundary is given by a (linear) hyperplane. Such a hyperplane is given by the set x|wtx=b which thus splits Rn into two classes, x|wtx≤b and x|wtx>b.
Detailed explanation-4: -The perceptron outputs 1 for any input point above the hyperplane, and outputs 0 for any input on or below the hyperplane. For this reason, the perceptron is called a linear classifier, i.e., it works well for data that are linearly separable.