Cross-Validation is a method of evaluating and comparing predictive systems in statistics and machine learning.
As from the title I am wondering what is the difference between StratifiedKFold with the parameter shuffle = True StratifiedKFold(n_…
python scikit-learn cross-validationAttempting to create a decision tree with cross validation using sklearn and panads. My question is in the code below, …
machine-learning decision-tree cross-validationWorking with Sklearn stratified kfold split, and when I attempt to split using multi-class, I received on error (see below). …
python machine-learning keras scikit-learn cross-validationDoes the cross_val_predict (see doc, v0.18) with k-fold method as shown in the code below calculate accuracy for …
python scikit-learn cross-validationI want to evaluate a regression model build with scikitlearn using cross-validation and getting confused, which of the two functions …
python machine-learning scikit-learn regression cross-validationI am following the IRIS example of tensorflow. My case now is I have all data in a single CSV …
python tensorflow cross-validation train-test-splitI would like to use the xgboost cv function to find the best parameters for my training data set. I …
python cross-validation xgboostLet's say I've read in a textfile using a TextLineReader. Is there some way to split this into train and …
tensorflow cross-validation training-dataI'm clustering documents using topic modeling. I need to come up with the optimal topic numbers. So, I decided to …
r tm cross-validation topic-modelingI am trying to optimize a logistic regression function in scikit-learn by using a cross-validated grid parameter search, but I …
python machine-learning scikit-learn cross-validation logistic-regression