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src/d/r/dragnet-HEAD/dragnet/model_training.py   dragnet(Download)
        model provides model.make_features to make the features
        from mozsci.map_train import run_train_models
        # to train the model need a set of all the features and their labels
        if self.weighted:
            errors = run_train_models(processes=4, model_library=model_library,
                X=features, y=labels, folds=folds, weights=weights)
            errors = run_train_models(processes=4, model_library=model_library,

src/m/o/mozsci-HEAD/test/test_map_train.py   mozsci(Download)
import unittest
import numpy as np
from mozsci.map_train import TrainModelCV, run_train_models
          [LogisticRegression, classification_error, None, (), {'lam':50}]]
        errors = run_train_models(2, model_library, X=self.X, y=self.y)
        for k in errors.keys():
            if re.search("{'lam': 0.5}", k):