Linear FA Value Predict

Problem

Predict a value with a linear function approximator that includes a bias.

weights[0] is the bias and weights[i + 1] multiplies features[i]: return weights[0] + w[1:] . features.

Hint

The first weight is a constant feature equal to one.

case 1

in: [[1,2,3],[4,5]]

expected: 24

case 2

in: [[0,0],[1]]

expected: 0

case 3

in: [[2,-1,0.5],[2,4]]

expected: 2

case 4

in: [[5],[]]

expected: 5

Starter codePython

def linear_value_predict(weights, features):
    # Your code here
    pass

4 test cases · run your code against them in the editor