Question

Which of the following statements is false:
a. The chances of overfitting decrease with Increasing the number of hidden nodes and increasing the number of hidden layers.
b.A neural network with one hidden layer can represent any Boolean function given sufficient number of hidden units and appropriate activation functions. c.Two hidden layer neural networks can represent any continuous functions (within a tolerance) as long as the number of hidden units is sufficient and appropriate activation functions used.

Answer 1

Explanation:

neural network with one hidden layer can represent any Boolean function given sufficient number of hidden units and

Answer 2

Answer :

b) A neural network with one hidden layer can represent any Boolean function given sufficient number of hidden units and appropriate activation functions.

Explanation :

• Because, To begin with, a single neuron can represent a non-monotonous Boolean function using a polynomial as the transfer function. Second, by encoding the binary values of the Boolean variables, the number of inputs in the neural network can be reduced.

• Two hidden layer neural networks can represent any continuous functions (within a tolerance) as long as the number of hidden units is sufficient and appropriate activation functions used. Is true, Due to Any function can be approximated to arbitrary accuracy by a network with two hidden layers.

• The chances of overfitting decrease with Increasing the number of hidden nodes and increasing the number of hidden layers. Is True due to Increasing the number of hidden layers might improve the accuracy or might not, it really depends on the complexity of the problem that you are trying to solve.