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- Cross Validated
Q A for people interested in statistics, machine learning, data analysis, data mining, and data visualization
- Tour - Cross Validated
Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization It is built and run by you as part of the Stack Exchange network of Q A sites
- machine learning - Difference between train test and . . . - Cross Validated
In this kind of situations, I am used to work with a train test split, performing cross-validation over the training sample in order to find the penalization parameter that reduces the prediction error, and once I found the optimal $\lambda$ I compute the actual prediction error over the test split
- classification - What do Cross Validation results actually tell about . . .
Part of the standard K-fold cross-validation procedure is shuffling the data at random For each random permutation you get a different result This variation tells you something about the variance of the estimate you obtain for the score risk etc
- Newest Questions - Cross Validated
Much higher scoring metrics with classification_report than cross_validate more hot questions
- machine learning - Purpose of Nested Cross-Validation? - Cross Validated
"Nested CV to testing data" is similar to "CV to validation data" Validation data is used to tune hyperparameters and prevent overfitting CV lets us get multiple copies of validation data (ideally different) So we our parameter selection process can be more robust
- Cross validation and parameter tuning - Cross Validated
To summarize: cross-validation by itself is used to asses performance of the model on out-of-sample data, but can also be used to tune hyper-parameters in conjunction with one of the search strategies in hyper-parameters space
- How to use cross_val_score in Scikit-Learn? - cross validation
I've been using cross_val_score in the Scikit-Learn package, along with Pandas dataframes and Numpy to find a 5 fold cross validation error for training a Linear Regression model on a sample data
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