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Questions tagged [grid-search]

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4
votes
3answers
43 views

Default parameters for decision trees give better results than parameters optimised using GridsearchCV

I am using Gridsearch for a DecisionTreeClassifier predicting a binary outcome. When I run fit and predict with default parameters, I get the following results: ...
1
vote
1answer
31 views

Logloss vs Accuracy. Which needs to be chosen to evaluate the model performance

While model tuning using Cross validation and Grid search , I was plotting the graph of different learning rate against logloss and accuracy separately. Graph of Logloss --> learning Rate When I ...
5
votes
1answer
53 views

How to plot mean_test score and mean_train score of GridSearchCV

How to plot mean_train_score and mean_test_score values in GridSearchCV for ...
1
vote
1answer
23 views

Optimizing decision threshold on model with oversampled/imbalanced data

I'm working on developing a model with a highly imbalanced dataset (0.7% Minority class). To remedy the imbalance, I was going to oversample using algorithms from imbalanced-learn library. I had a ...
1
vote
1answer
39 views

Scikitlearn grid search random forest using oob as metric?

Have looked at data on oob but would like to use it as a metric in a grid search on a Random Forest classifier (multiclass) but doesn't seem to be a recognised scorer for the scoring parameter . I do ...
0
votes
0answers
23 views

How to perform platt scaling for hyperparameter-optimized model?

I'm using Python and have a best estimator from a grid search. Wanted to be able to calibrate the probability output accordingly, but would like to know more about implementing platt scaling. From ...
0
votes
0answers
58 views

Model Selection with Oversampling/ Cross-Validation leads to similar test results in 2 approaches

Quick Intro Sorry for the long read. I added a lot in here because I wanted to describe what I've worked on so far, but I wanted to quickly summarize the issue I've been having, just so you have it ...
0
votes
0answers
81 views

Two different approaches of oversampling data with GridSearchCV leads to similar test results

I was trying to compare two approaches to optimal selection of hyperparameters based on two approaches: 1) Wrong Approach: Oversampling before GridSearch CV This can lead to bleeding of data (that ...
1
vote
0answers
104 views

Different values from GridSearch estimation

I am using GridSearchCV in order to find best estimator with best hiperparameters. I also want to check it once against a small portion of data used in cross ...
0
votes
1answer
290 views

GridSearch mean_test_score vs mean_train_score

I am working with scikit learn and GridSearch in order to find the best parameters in my classifiers. I have a map of different hyperparameters and I want to print out GridSearch results, but I do ...
3
votes
1answer
929 views

Why is cross-validation score so low?

I am using Scikit-Learn for this classification problem. The dataset has 3 features and 600 data points with labels. First I used Nearest Neighbor classifier. ...
4
votes
1answer
808 views

How to estimate GridSearchCV computing time?

If I know the time of a given validation with set values, can I estimate the time GridSearchCV will take for n values I want to cross-validate ?
0
votes
1answer
487 views

How to use GridSearchCV with RidgeClassifier

I'm trying to use GridSearchCV with RidgeClassifier, but I'm getting this error: My problem is regression type. IndexError: ...
2
votes
2answers
75 views

Comparison of machine learning approaches for a topic in a scientific paper

As part of my master's thesis, I have made a prediction of data with approaches of machine learning in a topic where are no papers yet. The topic is a regression problem for which several machine ...
2
votes
1answer
147 views

Parameter tuning for machine learning algorithms

When it comes to the topic of tuning parameters, most of the time you read grid search. But if you have 6 parameters, for which you want to test 10 variants, you get to 10^6 = 1000000 runs. Which in ...
1
vote
2answers
1k views

Class weight ineffective in sklearn

I'm dealing with an imbalanced dataset and as usual it's very easy to obtain a high accuracy, but the recall on the less frequent class is very low. I would like to improve on the false negative of ...
3
votes
1answer
858 views

Splitting hold-out sample and training sample only once?

I have a question related to evaluating out-of-sample predictions. For my research I want to tune two parameters related to Support Vector Machines, and use these optimized parameters to predict the ...
3
votes
1answer
305 views

Grid seach is unavailable for Keras in case of multiple outputs?

I do experiments with the following Keras architecture with multiple outputs: ...