Questions tagged [gridsearchcv]
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Need an example of a custom class whose instance is fed to sklearn Pipeline / make_pipeline to use with GridSearchCV
According to sklearn.pipeline.Pipeline documentation, the class whose instance is a pipeline element should implement fit() and transform(). I managed to create a custom class that has these methods ...
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random_state on train_test_split() appears to have large effect in performance metrics?
To summarize the problem: I have a data set with ~1450 samples, 19 features and a binary outcome where classes are fairly balanced (0.51 to 0.49).
I split the data into a train set and a test set ...
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How to perform Grid Search on NLP CRF model
I am trying to perform hyperparameter tuning on sklearn_crfsuite.CRF model. When I try to execute below code, it doesn't give any exception but it probably fails to perform fit. And due to which, if I ...
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Why is gridsearchCV.best_estimator_.score giving me r2_score even if I mentioned MAE as my main scoring metric?
I have a lasso regression model with the following definition :
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gridsearchcv best coefficients do not match well with the perfect line
I wrote a program to find the best combination of coefficients to describe a variable. However, the coefficients from the gridsearchcv do not match well with the expected line. This is a sample of my ...
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Multiple values for a single parameter in the mlflow run command
How to pass multiple values to each parameter in the mlflow run command?
The objective is to pass a dictionary to GridSearchCV as a param_grid to perform cross validation.
In my main code, I retrieve ...
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Query regarding surprising spike in accuracy of ML model
I implemented all the major ML models (Logistic Regression, Naive Bayes, SVM, KNN, Decision Tree, Random Forest, Ada Boost & XGBoost) on my dataset. My stratified cross-validation scores are ...
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Comparing accuracies of Grid Search CV & Randomized Search CV with K-Fold Cross Validation?
Are Grid Search CV & Randomized Search CV always/necessarily supposed to give more accurate results after hyperparameter tuning as compared to K-Fold Cross Validation?
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Does hyperparameter tuning of Decision Tree then use it in Adaboost individually vs Simultaneously yield the same results?
So, my predicament here is as follows, I performed hyperparameter tuning on a standalone Decision Tree classifier, and I got the best results, now comes the turn of Standalone Adaboost, but here is ...
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How to pick best model based on Accuracy and Recall in a GridSearchCV when you have already set scoring = custom_scorer?
This is a binary classification problem, I am using a GridSearchCV from Sklearn to find the best model, here is the GridSearch line I am using:
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n_jobs=-1 or n_jobs=1?
I am confused regarding the n_jobs parameter used in some models and for CV. I know it is used for parallel computing, where it includes the number of processors specified in n_jobs parameter. So if I ...
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What would be a good n_estimators matrix and thus param_grid for this problem?
I am using GridSearchCV for optimising my predictions
I am running a fairly large dataset and I am afraid I have not optimised the parameters enough.
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Can I run this job quicker for GridSearchCV?
I am using GridSearchCV for optimising my predictions and its been 5 hours now that the process is running.
I am running a fairly large dataset and I am afraid I ...
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288
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Worse performance after Hyperparameter tuning
I first construct a base model (using default parameters) and obtain MAE.
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Different values of mean absolute error when using GridSearchCV for max_leaf_nodes vs manually optimising max_leaf_nodes
I am trying out hyperparameter tuning vs manually selecting the best parameter (max_leaf_nodes) on a decision tree model with mean absolute error as the scoring. In ...
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My own model trained on the full data is better than the best_estimator I get from GridSearchCV with refit=True?
I am using an XGBoost model to classify some data. I have cv splits (train, val) and a separate test set that I never use until the end.
I have used GridSearchCV to determine the best parameters and ...
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GridSearchCV and time complexity
So, I was learning and trying to implement a GridSearch. I have a question regarding the following code, which I wrote:
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Specifying parameter grid for regression model
I am working with more than one dataset. So, I have to test my Random Forest Model over 4 datasets. The parameter grid I am taking for dataset D1 is not producing good results for dataset D2 and so on....
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Why GridSearchCV returns nan?
I am using gridsearchcv to tune the parameters of my model and I also use pipeline and cross-validation. When I run the model to tune the parameter of XGBoost, it returns ...
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Geolocation Based Anomaly Detection in IPs Using Isolation Forest
I'm trying to detect anomalies based on geolocation from IP addresses on a server access log file. I have created two features country and geo_velocity, using the IP address and the timestamp of each ...
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GridSearchCV with custom tune grid
What is the best way to perform custom parameter search CV with the Scikit-learn API? I really like GridSearchCV. However for my case the param_grid parameter is ...
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GridSearchCV using pre-defined validation dataset for KerasCNN return Warning about function
I want to use GridSearchCV for search best parameters for my CNN models to detect ECG anomaly. I have two dataframe which defined as train and test datasets, since want to follow previous research, ...
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Grid Search Pool Classifiers for Dynamic Classifier Selection Ensembles
I would like to grid search pool classifiers hyper parameter of OLA() ( Overall Local Accuracy ) model from deslib python package.
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Does GridSearchCV not save the best parameters?
So I tuned the hyperparameters using GridSearchCV, fitted the model to the data, and then used best_params_. I'm just curious ...
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When using GridSearchCV with regression tree how to interpret mean_test_score?
I am using GridSearchCV to tune hyperparameters of regression decision tree. When I do, I get mean_test_score but I thought it would return mean MSE since it is a regressor. how to interpret ...
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How to refit GridSearchCV on Multiclass problem
I'm trying to use GridSearchCV for my Multiclass problem. For starters, wanted to test it on KNeighborsClassifier.
First, here's the code where I define the function which uses GridSearchCV:
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GridSearchCV Acting Weird
I am using GridSearchCV to find the best combination of parameters for SVM. However, the parameters chosen by GridSeasrchCV do not seem to be the best ones. I tried some parameters randomly and they ...
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Hyper tuning reduce the accuracy score, why?
I have performed hyper tuning grid CV search on KNN model. The actual accuracy score for my KNN was accuracy of 42.31 % without performing hyper tuning. However, after performing hyper tuning, the ...
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466
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RandomizedSearchCV() not scoring all fits
I'm experiencing an issue with a RandomizedSearchCV grid that is not able to evaluate all of the fits. 50 of the 100 fits I'm calling do not get scored (score=nan), so I'm worried I'm wasting a bunch ...
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Error in using sklearn's GridSearchCV on Word2Vec
I am using the sklearn_api of gensim to create an estimator for a Word2vec model to pass it to sklearn's gridsearch . My code is as follows :
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Faster grid search with small dataset to derive best params instead of full dataset?
I have a dataset of 300 000 rows and an ensemble model, which include grid search to find the best params of every algorithm. Unfortunately the grid search needs to long and I have problems to ...
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i'm using GridSearchCV to find parameter C for SVC() classifier present in sklearn.svm . I'm not getting the optimal result desired
this is a screenshot of my code. i used abc.best_estimator_ (my GridSearchCV model) to find out best results. As you can see grid has values of C=1 and C=100 along with other values. abc....
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Getting unexpected keyword error in CatBoostRegressor while using GridSearchCV
I am trying to use GridSearchCV on a CatBoostRegressor algorithm, but get some "unexpected keyword" errors on 3 different params (classes_count, auto_class_weights, and bayesian_matrix_reg) ...
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What's the difference between GridSearchCrossValidation score and score on testset?
I'm doing classification using python. I'm using the class GridSearchCV, this class has the attribute best_score_ defined as "Mean cross-validated score of the best_estimator".
With this ...
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378
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Getting lower performance metrics when using GridSearchCV
I have defined an XGBoost model and would like to tune some of its hyperparameters.
I am using GridSearchCV to find the best params. However, I also tried to fit the model on the entire training ...
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How to compute AUC in gridsearchSV (multiclass problem)
I'm working on a multiclass classification problem, comparing results from SVM and Random Forest classificators. I would like to use gridsearchCV for hyperparameters tuning and find that AUC is the ...
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How is the GridsearchCV Score calculated?
How is the score of GridsearchCV calculated? Is the score a percentage? Does this mean higher is a better?
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Do i need to use hyperparamters from Gridsearch to train on WHOLE training set to get final model?
I just want to make sure i am on the right lines so please correct me if wrong. I am testing which hyperparmets are best for logisitic regession on my data X, y where X is featrues and y is target. X, ...
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EarlyStopping in GridSearch - how to get the mean epoch after which training stopped?
is there a way to get the mean number of epochs when training stopped by EarlyStopping in GridSearch?
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Feature Importance from GridSearchCV
I created a GridSearchCV for a Random Forest Regressor. Now I want to check the feature importance. I searched around and I found this:
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Search for hyperparameters whith different features using Random Forest
I have a dataset in which I would like to perform a classification model, so I have decided to use Random Forest. The number of features that I have is approximately 200 and I would like to test which ...
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How many trees does a Random Forest need?
At first, I did a GridsearchCV and the best parameter I found was 100, i.e., a random forest with just 100 trees. My trainset has 80,000 rows and 669 columns. My test set has 20,000 rows and 669 ...
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Is it alright to split a GridSearchCV?
Is it ok to split a GridsearchCV?
At first, I would try estimators from 100-300 (100 steps) for a random forest regressor and some other parameters and after that, I would start the GridsearchCV with ...
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Why does my GridSearchCV always break up?
GridSearchCV for my Random Forest breaks up. I need to know the reason and the solution to make it work:
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How to plot number of Trees and OOBs score with Grid Search
I searched to find the answer but I don´t find something with Grid Search.
I create a random forest and gradient boosting regressor with grid search. Now I want to make a visualization to see if the ...
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Can we apply to GridSearchCV to Logistic regression .?
When I apply GridSearchCV to my model Logistic Regression, it's continuously throwing below error.
I understand that it's trying to convert string to float. But that's was my data. So how can I ...
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Is GridSearchCV in combination with ImageDataGenerator possible and recommendable?
I want to optimize some hyperparameters for a CNN architecture by using GridSearchCV (Scikit-Learn) in combination with Data Augmentation (ImageDataGenerator from Keras).
However, GridSearchCV only ...
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Which combination of 3 hyperparameters to combat overfitting of a convolutional neural network?
I have a small dataset with which I want to train a CNN by using Data Augmentation. Since the CNN is overfitting due to the small data set, I would like to optimize some hyperparameters.
However, ...
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How to combine GridSearchCV with Early Stopping?
I'm a beginner in machine learning and want to train a CNN (for image recognition) with optimized hyperparameter like dropout rate, learning rate and number of epochs.
The optimal hyperparameter I ...
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