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I trained my model using different regression techniques, and I'm not sure which model to choose based on the learning curve.

1) Should I choose Lasso, since train and CV converge at the end 2) Should I choose Gradient Boosting since train and CV converge in the middle, and achieves a lower RMSE score than Lasso

Learning Curve: RMSE Score vs Number of Samples

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You should go for LightGBM which has the lowest training and cross validation RMSE. By the way, score is a bad name for RMSE because you would expect a higher score to mean that your model is better but here the opposite is true.

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