AutoML select the model manually

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It is been a while I am looking for the best pipeline to do some classification using AutoML. But I want to know if it is possible to select the model manually and then just optimize its hyperparameters. For example, I want to just optimize SVM's hyperparameters and don't care about other models.

knn hyperparameters automl svm optimization
1 Answers

You can optimize only the selected model in MLJAR AutoML. It is open-source AutoML with code available at GitHub: https://github.com/mljar/mljar-supervised

The example code will look like:

automl = AutoML(algorithms=["Xgboost"], mode="Compete")
automl.fit(X, y)

The above code will tune only the Xgboost algorithm. The mode Compete is needed because the MLJAR AutoML can work in three modes: Explain, Perform, and Compete. Algorithms available in MLJAR AutoML: Baseline, Linear, Random Forest, Extra Trees, Decision Tree, Neural Networks, Nearest Neighbors, Xgboost, LightGBM, CatBoost.

I'm the author of MLJAR AutoML, I'll be happy to help you set it and run.

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