Exam AI-900 topic 1 question 2 discussion

Vote for 'B' A. Use features for training and labels for evaluation. ==> Wrong (Training need both features and labels) B. Randomly split the data into rows for training and rows for evaluation. ==> Correct (few data used for training and on few data we can evaluate performance of model) , (so split in rows) C. Use labels for training and features for evaluation. ==> Wrong (for training we need both features and labels) D. Randomly split the data into columns for training and columns for evaluation. ==> Wrong (Data will be split row -wise)

give answer is correct, you can randomly split rows in order to have a variable sample to train and to evaluate the model ref: https://trainingsupport.microsoft.com/en-us/profile/131fc8db-0030-419a-bd97-531e612b2691

Correct Answer: B

B. Randomly split the data into rows for training and rows for evaluation.

Answer is B

training vs evaluation ratio: 70% vs 30%

B is correct

B makes sense

B is correct

Split the data for training and testing. randomly 75-25 split on row may be a good idea.

B est correct

give answer is correct, you can randomly split rows in order to have a variable sample to train and to evaluate the model

Absolutely B!

that is correct answer

Split the dataset into 2 parts with random rows

Correct option is B

B is Correct