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This repository was archived by the owner on May 25, 2024. It is now read-only.
This repository was archived by the owner on May 25, 2024. It is now read-only.

Can we use micromlgen with xgboost itself - without XGBClassifier #7

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@karimkhanvi

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@karimkhanvi

micromlgen works well with XGBClassifier. Which is imported from xgboost.

from xgboost import XGBClassifier

But in my program, I am using xgboost without any importa like this

import xgboost as xgb
model = xgb.cv(param,dtrain,num_boost_round=420,nfold=10,stratified=True,verbose_eval=20)
model = xgb.train(param,dtrain,420,[(dtrain,'train')],verbose_eval=20)

I tried using port on model, which gives me error

Traceback (most recent call last):
  File "model_microml_training.py", line 161, in <module>
    predict(sys.argv[1])
  File "model_microml_training.py", line 151, in predict
    print(port(model))
  File "/home/admin/dawid_venv_xgboost_1.1.0/lib/python3.5/site-packages/micromlgen/micromlgen.py", line 45, in port
    raise TypeError('clf MUST be one of %s' % ', '.join(platforms.ALLOWED_CLASSIFIERS))
TypeError: clf MUST be one of SVC, OneClassSVC, RVC, SEFR, DecisionTree, RandomForest, GaussianNB, LogisticRegression, PCA, PrincipalFFT, LinearRegression, XGBClassifier

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