{"id":54389,"date":"2024-04-16T00:09:21","date_gmt":"2024-04-16T00:09:21","guid":{"rendered":"https:\/\/exam.pscnotes.com\/mcq\/?p=54389"},"modified":"2024-04-16T00:09:21","modified_gmt":"2024-04-16T00:09:21","slug":"what-is-the-process-of-splitting-a-dataset-into-a-training-set-and-a-test-set-used-for-machine-learning-called","status":"publish","type":"post","link":"https:\/\/exam.pscnotes.com\/mcq\/what-is-the-process-of-splitting-a-dataset-into-a-training-set-and-a-test-set-used-for-machine-learning-called\/","title":{"rendered":"What is the process of splitting a dataset into a training set and a test set used for machine learning called?"},"content":{"rendered":"

[amp_mcq option1=”Data Partitioning” option2=”Data Sampling” option3=”Data Splitting” option4=”Data Shuffling” correct=”option1″]<\/p>\n

The correct answer is A. Data Partitioning.<\/p>\n

Data partitioning is the process of splitting a dataset into two or more subsets. The most common type of data partitioning is to split the dataset into a training set and a test set. The training set is used to train the machine learning model, and the test set is used to evaluate the model’s performance.<\/p>\n

Data sampling is the process of selecting a subset of data from a larger dataset. Data sampling can be used to reduce the size of a dataset, to improve the performance of machine learning algorithms, or to make the dataset more representative of the population from which it was drawn.<\/p>\n

Data splitting is the process of dividing a dataset into two or more subsets. Data splitting can be used to improve the performance of machine learning algorithms by reducing overfitting. Overfitting occurs when a machine learning model learns the training data too well and is not able to generalize to new data.<\/p>\n

Data shuffling is the process of randomly rearranging the order of data points in a dataset. Data shuffling can be used to improve the performance of machine learning algorithms by preventing the model from learning the order of the data points.<\/p>\n

In conclusion, the process of splitting a dataset into a training set and a test set used for machine learning is called data partitioning.<\/p>\n","protected":false},"excerpt":{"rendered":"

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