Artificial Intelligence MCQs

Page No. 59

What is the name of the function in the following statement “A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0”?


aStep function


bHeaviside function


cLogistic function


dPerceptron function


View Answer Heaviside function

A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0.


a True


bFalse


c Sometimes – it can also output intermediate values as well


dCan’t say


View Answer True

Neural Networks are complex ______________ with many parameters.


aLinear Functions


bNonlinear Functions


cDiscrete Functions


dExponential Functions


View Answer Linear Functions

Which of the following is not the promise of artificial neural network?


a It can explain result


bIt can survive the failure of some nodes


c It has inherent parallelism


dIt can handle noise



Why are linearly separable problems of interest of neural network researchers?


aBecause they are the only class of problem that network can solve successfully


bBecause they are the only class of problem that Perceptron can solve successfully


cBecause they are the only mathematical functions that are continue


dBecause they are the only mathematical functions you can draw



What is back propagation?


aIt is another name given to the curvy function in the perceptron


bIt is the transmission of error back through the network to adjust the inputs


cIt is the transmission of error back through the network to allow weights to be adjusted so that the network can learn


dNone of the mentioned



Why is the XOR problem exceptionally interesting to neural network researchers?


aBecause it can be expressed in a way that allows you to use a neural network


bBecause it is complex binary operation that cannot be solved using neural networks


cBecause it can be solved by a single layer perceptron


d Because it is the simplest linearly inseparable problem that exists.



Which of the following are the advantage/s of Decision Trees?


aPossible Scenarios can be added


bUse a white box model, If given result is provided by a model


cWorst, best and expected values can be determined for different scenarios


dAll of the mentioned


View Answer All of the mentioned

End Nodes are represented by __________


aDisks


bSquares


cCircles


dTriangles


View Answer Triangles

Chance Nodes are represented by __________


aDisks


bSquares


cCircles


dTriangles


View Answer Circles

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