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Recognizing Handwritten Digits
Train Test Split
In Python, the train_test_split function, part of the sklearn.model_selection module, is frequently utilized for dividing a dataset into two parts: a training subset and a testing subset.
This train_test_split() function performs a random partitioning of the dataset into these subsets, determined by a predefined test size or train size.
Task
- Split the dataset into training and test sets. Use only the first 1000 samples for splitting.
- Print the shapes and sizes of the resulting training and test sets for both the feature matrix and the target vector.
Task
- Split the dataset into training and test sets. Use only the first 1000 samples for splitting.
- Print the shapes and sizes of the resulting training and test sets for both the feature matrix and the target vector.
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In Python, the train_test_split function, part of the sklearn.model_selection module, is frequently utilized for dividing a dataset into two parts: a training subset and a testing subset.
This train_test_split() function performs a random partitioning of the dataset into these subsets, determined by a predefined test size or train size.
Task
- Split the dataset into training and test sets. Use only the first 1000 samples for splitting.
- Print the shapes and sizes of the resulting training and test sets for both the feature matrix and the target vector.
Switch to desktop for real-world practiceContinue from where you are using one of the options below