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Supervised Learning Questions and Answers

1.

A single layer perception cannot compute the following logical function :

Exam Year(s)

MH SET - 2023, SET Exam - 2023,

Answer: C

A single layer perceptron cannot compute XOR.

A single layer perceptron computes a linear threshold function: it outputs 1 on one side of a straight line (a hyperplane) and 0 on the other. It can therefore represent only linearly separable functions.

AND, OR and NOT are linearly separable; for AND, for example, the line \(x_1 + x_2 = 1.5\) separates (1, 1) from the other inputs. XOR outputs 1 for (0, 1) and (1, 0) and 0 for (0, 0) and (1, 1), and no single straight line separates these two pairs. Minsky and Papert's analysis of this limitation is well known, and it is solved by adding a hidden layer.

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2.

Which of the following data is linearly separable ?

Exam Year(s)

MH SET - 2023, SET Exam - 2023,

Answer: D

The linearly separable data is in plot (D).

Data are linearly separable when one straight line puts all points of one class on one side and all points of the other class on the other side.

In plot (D) all the crossed circles lie towards the lower right, and all the plain circles towards the upper left, so a straight line running from the lower left to the upper right between them separates the two classes.

In each of the other plots a point of one class lies between points of the other. In (A) a crossed circle sits between two plain circles on the left, in an XOR-like pattern; in (B) a crossed circle on the right lies between two plain circles; and in (C) the two classes are interleaved in the same quadrant. No single line separates them.

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