I want to implement a custom loss function in scikit learn. I use the following code snippet: def my_custom_loss_func(y_true,y_pred): diff3=max((abs(y_true-y_pred))*y_true) return diff3 score=m...

Grid search is a way to find the best parameters for any model out of the combinations we specify. I have formed a grid search on my model in the below manner and wish to find best parameters ident...

I have the following code which works normally but got a UserWarning: One or more of the test scores are non-finite: [nan nan] category=UserWarning when I revised it into a more concise version (...

Problem: My situation appears to be a memory leak when running gridsearchcv. This happens when I run with 1 or 32 concurrent workers (n_jobs=-1). Previously I have run this loads of times with no t...

Is it possible to see the progress of GridSearchCV in a Jupyter Notebook? I'm running this script in python: param_grid = {'learning_rate': [0.05, 0.10, 0.15, 0.20, 0.25, 0.30] , 'max_depth' : [3,...

In scikit-learn 0.24.0 or above when you use either GridSearchCV or RandomizedSearchCV and set n_jobs=-1, with setting any verbose number (1, 2, 3, or 100) no progress messages gets printed. Howeve...

When faced with a large dataset, I need to spend a day using GridSearchCV() to train an SVM with the best parameters. How can I save the best estimator so that I can use this trained estimator dire...

Which one among Gridsearchcv and Bayesian optimization works better for optimizing hyper parameters?

I am trying to use OnClassSVM for anomaly detection purpose and I tuned its parameters using GridSearchCV() as follows: I have searched many sites for it including https://stackoverflow.com/ but c...

I am using scikit-learn library and building a pipeline from it. This is the last (and main) part of pipeline that I build: preprocessor_steps = [('data_transformer', data_transformer), ('reduce_d...

The Verbose arguement in the GridSearchCV function displays the processing steps for each execution. Las time when I used, it worked just fine. But when I ran the model today, the verbose steps are...

I did grid search + crossvalidation on a SVM with RBF kernel to find optimal value of parameters C and gamma using the class GridShearchCV. Now I would like to get the result in a tabular format li...

My question seems to be similar to this one but there is no solid answer there. I'm doing a multi-class multi-label classification, and for doing that I have defined my own scorers. However, in ord...

I wanted to find out the correct naming convention when referring to individual preprocessor included in ColumnTransformer (which is part of a pipeline) in param_grid for grid_search. Environment &...

Consider 3 data sets train/val/test. sklearn's GridSearchCV() by default chooses the best model with the highest cross-validation score. In a real-world setting where the predictions need to be acc...

I am struggling with a machine learning project, in which I am trying to combine : a sklearn column transform to apply different transformers to my numerical and categorical features a pipeline t...

What I am trying to do? I am trying to use StratifiedKFold() in GridSearchCV(). Then, what does confuse me? When we use K Fold Cross Validation, we just pass the number of CV inside GridSearchCV...

I often use GridSearchCV for hyperparameter tuning. For example, for tuning regularization parameter C in Logistic Regression. Whenever an estimator I am using has its own n_jobs parameter I am con...

I want to use StackingClassifier to combine some classifiers and then use GridSearchCV to optimize the parameters: clf1 = RandomForestClassifier() clf2 = LogisticRegression() dt = DecisionTreeClas...

I am using two estimators, Randomforest and SVM random_forest_pipeline=Pipeline([ ('vectorizer',CountVectorizer(stop_words='english')), ('random_forest',RandomForestClassifier()) ]) svm_pipeli...

As you can see, I have a problem with using sklearn (lightgbm, GridSearchCV). Please let me know how to solve this error. My code is the following: import lightgbm as lgb from lightgbm.sklearn impo...

I am doing topic modeling using sklearn. While trying to get the log-likelihood from Grid Search output, I am getting the below error: AttributeError: 'str' object has no attribute 'parameters'...

Thank you for answering in advance. This is my first post and I am relatively new to python, so I apologize if I have formatted something terribly. I am trying to combine recursive feature elimina...

tried grid.cv_results_ didnt correct problem from sklearn.model_selection import GridSearchCV params = { 'decisiontreeclassifier__max_depth': [1, 2], 'pipeline-1__clf__C': [0.001, 0.1, 100.0] } g...

I am trying to run GradientBoostingClassifier() with the help of gridsearchcv. For every combination of parameter, I also need "Precison", "recall" and accuracy in tabular format. Here is the code...