Reputation: 31
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.
Upvotes: 2
Views: 406
Reputation: 5839
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.
Upvotes: 3