Questions tagged [gridsearchcv]

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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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2answers
247 views

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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1answer
238 views

What to do after GridSearchCV()?

I happily created my first NN and performed hyperparameter optimization through GridSearchCV. I just don't know what to do next. Do I have to fit it again with the ...
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1answer
1k views

How to choose the model parameters (RandomizedSearchCV, .GridSearchCV) or manually

Faced with the task of selecting parameters for the lightgbm model, the question accordingly arises, what is the best way to select them? I used the RandomizedSearchCV method, within 10 hours the ...
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1answer
4k views

sklearn.GridSearchCV predict method not providing the best estimate and accuracy score

I was playing around with the credit default dataset in UCI ("https://archive.ics.uci.edu/ml/machine-learning-databases/00350/default%20of%20credit%20card%20clients.xls") These are the steps i have ...
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1answer
5k views

Using GridSearchCV and a Random Forest Regressor with the same parameters gives different results

As the huge title says I'm trying to use GridSearchCV to find the best parameters for a Random Forest Regressor and I'm measuring my results with mse. ...
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1answer
15 views

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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1answer
32 views

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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1answer
14 views

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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0answers
14 views

Which Random Forest hyperparameters to tune with Grid Search and which are the best initial hyperparameters values?

I want to use Grid Search for finding optimal hyperpameters for Random Forest. My questions are: Which Random Forest hyperparameters are considered important for tuning? Which initial Random Forest ...
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15 views

Grid Search using strategy

What is the correct strategy of using Grid Search? Am I understand correctly that to use correctly Grid Search I should: Give Grid Search initial parameters that have wide range. For example if ...
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0answers
85 views

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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1answer
146 views

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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1answer
603 views

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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192 views

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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2answers
185 views

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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0answers
274 views

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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0answers
96 views

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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0answers
464 views

Why do I have leakage while using Stratified Group K Fold?

I have the following case: Training data in the form of x, y coordinates on different frames (from a video). Based on this I computed some features, using only the training data and labels. A model is ...
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1answer
79 views

CNN for subsets of a dataset - how to tune hyperparameters

I have a dataset and would like to train CNNs on subsets of different size of the dataset. I already have a CNN, which classifies very well if I use the entire dataset. Now the question arises if I ...
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1answer
33 views

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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2answers
40 views

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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