CODEWITHSUNDEEP
pythonscikit-learnlogistic-regressionmlpauto-sklearn
asmgx
asmgx

Reputation: 8044

What is the code for Logistic Regression and MLP

I am trying to use AutoSklearn with a specific list of algorithms

Logistic Regression
Random Forest
Gaussian NB
SVC
ADA
MLP

I know I can use these parameters.

mdl = autosklearn.classification.AutoSklearn2Classifier(
    include = {
         'classifier': ["random_forest", "gaussian_nb", "libsvm_svc", "adaboost"],
         'feature_preprocessor': ["no_preprocessing"]
    #K-Folds?
    },
    exclude=None,

I managed to find the code for these algorithms

Random Forest  ==> "random_forest"
Gaussian NB  ==> "gaussian_nb"
SVC  ==> "libsvm_svc"
ADA  ==> "adaboost"

but could not find the codes for

Logistic Regression
MLP

can anyone tell me what are these?

Upvotes: 0

Views: 126

Answers (1)

Antoine Dubuis
Antoine Dubuis

Reputation: 5324

The documentation states that the strings used to identify estimators and preprocessors are the filenames without .py.

You can find here the model_id you are looking for here.

From the documentation MLP code is mlp, and Logistic Regression is not implemented. (see this issue for further information)

Therefore you should do as follows:

mdl = autosklearn.classification.AutoSklearn2Classifier(
    include = {
         'classifier': ["random_forest", "gaussian_nb", "libsvm_svc", "adaboost", 'mlp'],
         'feature_preprocessor': ["no_preprocessing"]
    },
    exclude=None
)

Upvotes: 2

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