All Questions
15 questions
0votes
0answers
273views
Correct method to report Randomized Search CV results
I have searched online but I still cannot find a definitive answer on how to "correctly" report the results from hyperparameter tuning a machine learning model; though, this may just be some ...
- 173
2votes
2answers
3kviews
Grid_search (RandomizedSearchCV) extremely slow with SVM (SVC)
I'm testing hyperparameters for an SVM, however, when I resort to Gridsearch or RandomizedSearchCV, I haven't been able to get a resolution, because the processing time is exceeding hours. My dataset ...
1vote
1answer
1kviews
How to train multioutput classification with hyperparameter tuning in sklearn?
I am working on a simple multioutput classification problem and noticed this error showing up whenever running the below code: ...
- 299
2votes
1answer
2kviews
how to prevent machine crash while searching for hyper parameters of XGBoost with GridSearchCV
I am searching for best hyper parameters of XGBRegressor using GridSearchCV. Here is the code: ...
0votes
1answer
2kviews
MLP classifier Gridsearch CV parameters to tune?
I'm looking to tune the parameters for sklearn's MLP classifier but don't know which to tune/how many options to give them? Example is learning rate. should i give it[.0001,.001,.01,.1,.2,.3]? or is ...
1vote
1answer
165views
Random Forest Model Giving Same Accuracy for different feature sets after tuning
I am having this weird issue and cannot seem to find a solution. I am trying to tune a different random forest model for every different feature-set. Basically from a given data set, I have created 3 ...
- 111
4votes
2answers
6kviews
GridSearchCV vs RandomSearchCV and How it works?
GridSearchCV vs RandomSearchCV Can somebody explain in-detailed differences between GridSearchCV and RandomSearchCV? And how the algorithms work under the hood? As per my understanding from the ...
- 4,143
1vote
1answer
9kviews
hyperparameter tuning with validation set
For what I know, and correct me if I am wrong, the use of cross-validation for hyperparameter tuning is not advisable when I have a huge dataset. So, in this case it is better to split the data in ...
- 227
1vote
0answers
49views
Minimizing overfitting when doing hyperparameter Tuning
Generaly when using Sklearn's GridSearchCV (or RandomizedGridSearchCV), we get best model with best test score even if the model overfits a little bit. How can we compute generalization error ...
7votes
1answer
4kviews
how to pass parameters over sklearn pipeline's stages?
I'm working on a deep neural model for text classification using Keras. To fine tune some hyperparameters i'm using Keras Wrappers for the Scikit-Learn API. So I builded a Sklearn Pipeline for that: <...
1vote
1answer
313views
Track underlying observation when using GridSearchCV and make_scorer
I'm doing a GridSearchCV, and I've defined a custom function (called custom_scorer below) to optimize for. So the setup is like this: ...
1vote
0answers
371views
How to put KerasClassifier, Hyperopt and Sklearn cross-validation together
I am performing a hyperparameter tuning optimization (hyperopt) tasks with sklearn on a Keras models. I am trying to optimize KerasClassifiers using the Sklearn cross-validation, Some code follows: <...
- 11
2votes
1answer
2kviews
XGBOOST (sklearn interface) REGRESSION error
I am trying to run a GRIDSEARCHCV (sklearn) on XGBRegressor. Documentation on the parameter says that if regression, then objective = reg:squarederror.(see https://...
- 1,101
7votes
1answer
4kviews
How to decide how many n_neighbors to consider while implementing LocalOutlierFactor?
I have a data set with rows: 134000 and columns: 200. I am trying to identify the outliers in data set using LocalOutlierFactor from scikit-learn. Although I ...
- 121
1vote
1answer
2kviews
Is there any alternative to L-BFGS-B algorithm for hyperparameter optimization in Scikit learn?
The Gaussian process regression can be computed in scikit learn using an object of class GaussianProcessRegressor as: ...
- 103
