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)

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)

rows are split, columns are not split.80:20 or 70:30 ratio for training and testing

B is correct

correct

vote foe C

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