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Machine Learning – Exploring the Model Q&A

What is the process of dividing each feature by its range called ?
Feature Scaling — Correct

Input variables are also known as feature variables.
True — Correct

Output variables are known as Feature Variables .
False — Correct

__ controls the magnitude of a step taken during Gradient Descent .
Learning Rate — Correct

The objective function for linear regression is also known as Cost Function.
True — Correct

What is the process of subtracting the mean of each variable from its variable called ?
Mean Normalization — Correct

For different parameters of the hypothesis function we get the same hypothesis function.
False — Correct

How are the parameters updates during Gradient Descent Process ?
Simultaneously — Correct

The result of scaling is a variable in the range of [1 , 10].
False — Correct

What is the Learning Technique in which the right answer is given for each example in the data called ?
Supervised Learning — Correct

Problems that predict real values outputs are called ?
Regression Problems — Correct

Cost function in linear regression is also called squared error function.
True — Correct

What is the name of the function that takes the input and maps it to the output variable called ?
Hypothesis Function — Correct


  1. GunjanGunjan

    Linear regression is an optimal function that can be used for classification problems
    false correct
    Underfit data has high variance
    False correct

    14 February 2021 at 2:27 pm Reply
  2. BhanuBhanu

    Problems, where discrete-valued outputs are predicted, are called? classification

    1 April 2021 at 3:42 am Reply

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