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Results tagged with cross-validation
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user 14582
Refers to general procedures that attempt to determine the generalizability of a statistical result. Cross-validation arises frequently in the context of assessing how a particular model fit predicts future observations. Methods for cross-validation usually involve withholding a random subset of the data during model fitting and quantifying how accurate the withheld data are predicted and repeating this process to get a measure of prediction accuracy.
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sckit-learn Cross validation and model retrain
I want to train a model and also perform cross validation in scikit-learn, If i want to access the model (For instance to see the parameter's selected and weights or to predict) i will need to fit it …
- 336
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Validation vs. test vs. training accuracy. Which one should I compare for claiming overfit?
I have read on the several answers here and on the Internet that cross-validation helps to indicate that if the model will generalize well or not and about overfitting.
But I am confused that which t …
- 336