Questions tagged [gridsearchcv]
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GridSearchCV with TimeSeriesSplit
I am tuning the HPs for a time dependant neural network model (heating energy consumption prediction) in a bachelor thesis.
Total amount of samples is 145.860, with minutely granularity from January ...
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How to pass a Dataframe as train dataframe and another dataframe as Validation to GridSearchCV
I'm a programmer who tries to find he's way into ML world. so the Question might be basic.
i have data from years 2010-2019. Now i'm trying to test different parameters on gradient boosting regression ...
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integration of Feature Selection in Pipeline
I have noticed integrating feature selection in a pipeline alters results.
Pipeline 1 gives slightly different results with pipeline 2. Why should this be so?
Pipeline 2
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Need insights in how to reduce overfitting with MLPClassifier
I am new to data science. Please bear with me as I ask this long question. I am trying to do Speech Emotion Recognition with MLPCLassifier on RAVDESS and Crema datasets. I am predicting only three ...
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GridSearchCV custom scorer to consider both train and test performance
Based on my current understanding, the standard use of GridSearchCV scorers ( through available options such as "f1_micro") aim to maximize the average performance across validation folds. ...
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Can I fit a model with the parameters found with RandomizedSearchCV?
I want to ask you a question.
Suppose I use the following RandomizedSearchCV to find the model's best hyperparams:
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Tuned model has higher CV accuracy, but a lower test accuracy. Should I use the tuned or untuned model?
I am working on a classification problem using Sci Kit Learn and am confused on how to properly tune hyper parameters to get the "best" model.
Before any tuning, my logistic regression ...
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Do we need to check the training score when we use randomizedsearchcv
given a model and a set of parameters, randomizedsearchCV(or gridsearchCV) gives the mean of the best scores from a list of different folds of the datasets.
Does the model control for overfitting? I ...
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Does sklearn perform feature selection within cross validation?
I would like to add a feature selector on my pipeline and use gridsearchcv to tune both the hyperparameters of the selector and the classifier(s).
I am wondering if sklearn performs feature selection ...
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How does GridSearchCV use Cross Validation to produce a Model's Score?
I understand Cross Validation in practice, but I'm not sure how SciKit-Learn's GridSearchCV uses it to produce an overall score/ metric for a model. For example, if ...
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Output of GridSearchCV
I read the documentation of the GridSearchCV from sklearn. I understand that when we use the fit and the predict, actually we are running them on the best model that GridSearchCV found. But can we use ...
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why when I find the best accuracy for logistic regression then it give me this error (AttributeError: split not found)
after run this code I face the split not found error.
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Grid Searching seed in randomized machine learning
I was wondering if tuning a seed with cross-validation in order to maximize the performance of an algorithm heavily based on a randomness factor is a good idea or not. I have created an Extra Tree ...
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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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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 [duplicate]
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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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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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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