KPMG ML Regression

Supervised, Unsupervised and Reinforcement are three types of Machine Learning

• True

• False

• May be

• None of the above

In Supervised learning

• Dependent variable is known

• Dependent variable is unknown

• Need to create dependent variable

• None of the above

In Unsupervised learning

• Dependent variable is known

• Dependent variable is unknown

• Need to create dependent variable

• None of the above

Linear Regression is used when

• Dependent variable is continues

• Dependent variable is categorical

• Dependent variable is not present

• None of the above

Y = mx + c is simple representation of linear regression

• True

• False

• May be

• None of the above

train test split is recommended before training of the machine learning algorithms

• True

• False

• May be

• Don't know

MAE, RMSE, MSE are all the evaluation matrix used for the linear regression

• True

• False

• May be

• None of the above

R2 score 0 (Zero) means best model

• True

• False

• May be

• None of the above

We can see imbalanced data in Linear regression

• True

• False

• May be

• Don't know

Linear regression is used for

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Deep Learning