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Tag model-selection - This is page 16 - GeneraCodice
Variance in cross validation score / model selection
https://www.generacodice.com/en/articolo/1124296/variance-in-cross-validation-score-model-selection
cross-validation
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model-selection
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xgboost
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parameter-estimation
datascience.stackexchange
Comparing SMOTE to down sampling the majority class in imbalanced binary classification
https://www.generacodice.com/en/articolo/1123551/comparing-smote-to-down-sampling-the-majority-class-in-imbalanced-binary-classification
classification
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unbalanced-classes
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cross-validation
-
model-selection
datascience.stackexchange
Is ROC and AUC the only criteria for choosing a model?
https://www.generacodice.com/en/articolo/1121686/is-roc-and-auc-the-only-criteria-for-choosing-a-model
model-selection
datascience.stackexchange
Nested cross-validation and selecting the best regression model - is this the right SKLearn process?
https://www.generacodice.com/en/articolo/1119995/nested-cross-validation-and-selecting-the-best-regression-model-is-this-the-right-sklearn-process
python
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scikit-learn
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cross-validation
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model-selection
datascience.stackexchange
Any “rules of thumb” on number of features versus number of instances? (small data sets)
https://www.generacodice.com/en/articolo/1116279/any-rules-of-thumb-on-number-of-features-versus-number-of-instances-small-data-sets
feature-selection
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model-selection
datascience.stackexchange
On coursera what exactly does Andrew Ng say in videos Lectures 60 & 61 of machine learning?
https://www.generacodice.com/en/articolo/1113592/on-coursera-what-exactly-does-andrew-ng-say-in-videos-lectures-60-61-of-machine-learning
machine-learning
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cross-validation
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model-selection
datascience.stackexchange
How do scientists come up with the correct Hidden Markov Model parameters and topology to use?
https://www.generacodice.com/en/articolo/1109695/how-do-scientists-come-up-with-the-correct-hidden-markov-model-parameters-and-topology-to-use
machine-learning
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markov
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hyperparameter
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model-selection
datascience.stackexchange
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