In machine learning, grid search refers to multiple runs to find the optimal value of parameter(s)/hyperparameter(s) of a model, e.g. mtry for random-forest or alpha, beta, lambda for glm, or C, kernel and gamma for SVM.
Questions tagged [grid-search]
865 questions
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Fitting sklearn GridSearchCV model
I am trying to solve a regression problem on Boston Dataset with help of random forest regressor.I was using GridSearchCV for selection of best hyperparameters.
Problem 1
Should I fit the GridSearchCV on some X_train, y_train and then get the best…
Rookie_123
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What does rank_test_score stand for from the model.cv_results_?
After I have built a model with GridSearchCV, I get the cross validation results with model.cv_results_. But among the results one parameter is confusing to me. What does rank_test_score stand for in this?
mean_fit_time …
JimminyCricket
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How to get all the models (one for each set of parameters) using GridSearchCV?
From my understanding:
best_estimator_ provides the estimator with highest score; best_score_ provides the score of the selected estimator; cv_results_ may be exploited to get the scores of all estimators.
However, it is not clear to me how to get…
pierluigisr
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GridsearchCV: can't pickle function error when trying to pass lambda in parameter
I have looked quite extensively on stackoverflow and elsewhere and I can't seem to find an answer to the problem below.
I am trying to modify a parameter of a function that is itself a parameter inside the GridSearchCV function of sklearn. More…
Eric F
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Pipeline and GridSearch for Doc2Vec
I currently have following script that helps to find the best model for a doc2vec model. It works like this: First train a few models based on given parameters and then test against a classifier. Finally, it outputs the best model and classifier (I…
Christopher
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Get standard deviation for a GridSearchCV
Before scikit-learn 0.20 we could use result.grid_scores_[result.best_index_] to get the standard deviation. (It returned for exemple: mean: 0.76172, std: 0.05225, params: {'n_neighbors': 21})
What's the best way in scikit-learn 0.20 to get the…
Neabfi
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Python: Gridsearch Without Machine Learning?
I want to optimize an algorithm that has several variable parameters
as input.
For machine learning tasks, Sklearn offers the optimization of hyperparameters with the gridsearch functionality.
Is there a standardized way / library in Python that…
user9098929
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2 answers
Hyperparameter in Voting classifier
So, I have a classifier which looks like
clf = VotingClassifier(estimators=[
('nn', MLPClassifier()),
('gboost', GradientBoostingClassifier()),
('lr', LogisticRegression()),
], voting='soft')
And I want to…
frazman
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How does 'max_samples' keyword for a Bagging classifier effect the number of samples being used for each of the base estimators?
I want to understand how max_samples value for a Bagging classifier effects the number of samples being used for each of the base estimators.
This is the GridSearch output:
GridSearchCV(cv=5, error_score='raise',
…
hkhare
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Grid search with f1 as scoring function, several pages of error message
Want to use Gridsearch to find best parameters and use f1 as the scoring metric.
If i remove the scoring function, all works well and i get no errors.
Here is my code:
from sklearn import grid_search
parameters =…
hmmmbob
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Sklearn: Evaluate performance of each classifier of OneVsRestClassifier inside GridSearchCV
I am dealing with multi-label classification with OneVsRestClassifier and SVC,
from sklearn.datasets import make_multilabel_classification
from sklearn.multiclass import OneVsRestClassifier
from sklearn.svm import SVC
from sklearn.grid_search…
Francis
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GridSearchCV scoring parameter: using scoring='f1' or scoring=None (by default uses accuracy) gives the same result
I'm using an example extracted from the book "Mastering Machine Learning with scikit learn".
It uses a decision tree to predict whether each of the images on a web page is an
advertisement or article content. Images that are classified as being…
Pablo Fleurquin
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Why GridSearchCV model results are different than the model I manually tuned?
this is my first question ever here I hope I am doing this right,
I was working on titanic dataset which is popular on kaggle, this tutarial if u wanna check A Data Science Framework: To Achieve 99% Accuracy
the part 5.2, it teaches how to…
Emre Yücel
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Combination of GridSearchCV's refit and scorer unclear
I use GridSearchCV to find the best parameters in the inner loop of my nested cross-validation. The 'inner winner' is found using GridSearchCV(scorer='balanced_accuracy'), so as I understand the documentation the model with the highest balanced…
Johannes Wiesner
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Ridge Regression Grid Search with Pipeline
I am trying to optimize hyperparameters for ridge regression. But also add polynomial features. So, pipeline looks okay but getting error when try to gridsearchcv. Here:
# Importing the Libraries
import numpy as np
import pandas as pd
import…
cepel
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