= Regression validation
{wiki=Regression_validation}
Regression validation refers to the process of assessing the performance and accuracy of regression models. It involves evaluating how well the model predicts outcomes based on known input data. This validation is crucial in ensuring that the developed regression model can generalize well to unseen data and provides reliable predictions. There are several techniques and metrics used in regression validation, including: 1. **Train-Test Split**: The dataset is split into two subsets, one for training the model and another for testing its performance.
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