- All Exams Instant Download
For a machine learning progress, how should you split data for training and evaluation?
For a machine learning progress, how should you split data for training and evaluation?
A . Use features for training and labels for evaluation.
B . Randomly split the data into rows for training and rows for evaluation.
C . Use labels for training and features for evaluation.
D . Randomly split the data into columns for training and columns for evaluation.
Answer: D
Explanation:
In Azure Machine Learning, the percentage split is the available technique to split the data. In this technique, random data of a given percentage will be split to train and test data.
Reference: https://www.sqlshack.com/prediction-in-azure-machine-learning/
Latest AI-900 Dumps Valid Version with 85 Q&As
Latest And Valid Q&A | Instant Download | Once Fail, Full Refund
Not right. According to Microsoft (se the enclosed link) you split rows not columns, so the answer should be B not D:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/split-data#how-to-configure-split-data