All Questions
44 questions
0votes
1answer
37views
Sklearn EstimatorCV vs GridSearchCV
sklearn has the following description for EstimatorCV estimators: https://scikit-learn.org/stable/glossary.html#term-cross-validation-estimator An estimator that has built-in cross-validation ...
0votes
0answers
23views
How to use cross validation to select/evaluate model with probability score as the output?
Initially I was evaluating my models using cross_val with out-of-pocket metrics such as precision, recall, f1 score, etc, or with my own metrics defined in ...
- 21
4votes
0answers
92views
Does ROC AUC different between crossval and test set indicate overfitting or other problem?
I am training a composite model (XGBoost, Linear Regression, and RandomForest) to predict injured people probability. Well, the results of cross-validation with 5 folds. Well, I can see any problem ...
- 116
0votes
0answers
362views
Split dataframe to a train and test sets with a cross validation of x%
I am working on a dataframe and need to split it into a training set and test set, with 90% for Cross-Validation training, and 10% for a final test set. The problem is that I do not know where to ...
1vote
0answers
112views
How to implement kfold and cv into Hybrid feature selection and evaluate the classification model performance?
I have been working on a Hybrid feature selection combined with hyperopt package for hyperparameter tuning and I am thinking about evaluating the performance of several model classifiers. I looked ...
- 111
3votes
2answers
1kviews
Understanding Sklearns learning_curve
I have been using sklearns learning_curve , and there are a few questions I have that are not answered by the documentation(see also here and here), as well as questions that are raised by the ...
- 181
0votes
1answer
8kviews
neg_mean_squared_error in cross_val_score [closed]
The string "mean_squared_error" appears to be deprecated in cross_val_score now, and it's saying to use ...
- 101
0votes
2answers
553views
What makes the validation set a good representative of the test set? [closed]
I am developing a classification model using an imbalanced dataset. I am trying to use different sampling techniques to improve the model performance. For my baseline model, I defined an AdaBoost ...
- 447
11votes
1answer
4kviews
Why you shouldn't upsample before cross validation
I have an imbalanced dataset and I am trying different methods to address the data imbalance. I found this article that explains the correct way to cross-validate when oversampling data using SMOTE ...
- 447
1vote
1answer
6kviews
Very low cross-val score for regression with big .corr() between feature and result
Im trying to make regression with sklearn between one feature and one result. This is the dataset that I have: ...
- 199
1vote
1answer
188views
How to transform predicted results when doing cross-validation in sklearn?
I want to do cross-validation in sklearn like below, but the predicted result of X still need to be transformed to reduce the distance from y. How to do that with adding a custom function? ...
- 111
1vote
2answers
564views
What is meaning of zip(kfold.split(X, Y) in sklearn
What is meaning of zip(kfold.split(X, Y) in sklearn? for (train, test)in zip(kfold.split(X, Y)):
- 1,896
2votes
2answers
455views
Advice and Ideas appreciated - Machine Learning one man project
I have a project where I am supposed to start from scratch and learn how machine Learning works. So far everything is working out better than expected but I feel as I am offered to many ways to choose ...
- 147
0votes
1answer
2kviews
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
1vote
1answer
226views
Splitting large multi class dataset using leave one out scheme into train and test
I am doing some supervised learning using neural networks, and i have a Targets array containing 1906 samples, which contain 664 unique values. min. count of each unique value==2, by design. Is there ...
- 41
