A model A has outputs of 0.2 and 0.6 at subsequent iterations of gradient descent. The model uses the sigmoid activation function at its output node. What is the differential of the output with respect to the net function at the mid-point between these two iterations?

A given neuron with a logistic activation function has two parameters w0=-1 and w1=-0.5 and rounds its output off to the nearest integer. What is the neuron's output for an instance with a descriptive feature value of -2?

Which of the following is an affine function? Select all that apply. Negative marking will be used for incorrect answers.

How many instances are in the test set derived from splitting the given dataset using a split ratio of 0.7?

How many Class B instances are in the train set derived from splitting the given dataset using a split ratio of 0.7?

What is the model prediction for an instance with descriptive features x1 = 0.31 and x2 = 0.46?

What is the model accuracy rate (a number in the range [0,1]) on the test set derived from splitting the given dataset using a split ratio of 0.7?

How many bias weights does the model have?

A given logistic regression model has two parameters w0=2 and w1=0.5 and it does not round its output off to the nearest integer. The training set has only one instance which has a descriptive feature value of -4 and a target value of 1. What is errorDelta for the descriptive feature at the end of one epoch of the gradient descent algorithm?