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Python 3
Understanding the Resulting Datasets

Understanding the Resulting Datasets

Understanding the Resulting Datasets

Understanding the Resulting Datasets

After splitting, four datasets are created:

Dataset	Purpose
X_train	Training features
X_test	Testing features
y_train	Training labels
y_test	Testing labels

For the California Housing Dataset:

Dataset	Approximate Size
X_train	16512 rows
X_test	4128 rows
y_train	16512 rows
y_test	4128 rows

The training data is used for learning, while the testing data remains untouched until evaluation.

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Understanding the Resulting Datasets

Contents

Understanding the Resulting Datasets

House Price Prediction Using Machine Learning (XGBoost)

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