APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Because it can be expressed in a way that allows you to use a neural network
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Because it is complex binary operation that cannot be solved using neural networks
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Because it can be solved by a single layer perceptron
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Because it is the simplest linearly inseparable problem that exists.
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Detailed explanation-1: -Q6. Why is the XOR problem exceptionally interesting to neural network researchers? A3. Because it is a complex binary function that cannot be solved by a neural network.
Detailed explanation-2: -The XOR, or “exclusive or”, problem is a classic problem in ANN research. It is the problem of using a neural network to predict the outputs of XOR logic gates given two binary inputs. An XOR function should return a true value if the two inputs are not equal and a false value if they are equal.
Detailed explanation-3: -A perceptron can only converge on linearly separable data. Therefore, it isn’t capable of imitating the XOR function.
Detailed explanation-4: -A “single-layer” perceptron can’t implement XOR. The reason is because the classes in XOR are not linearly separable. You cannot draw a straight line to separate the points (0, 0), (1, 1) from the points (0, 1), (1, 0).