forked from enviPath/enviPy
Basic System (#31)
Co-authored-by: Tim Lorsbach <tim@lorsba.ch> Reviewed-on: enviPath/enviPy#31
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@ -15,6 +15,7 @@ from pathlib import Path
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from dotenv import load_dotenv
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from envipy_plugins import Classifier, Property, Descriptor
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from sklearn.ensemble import RandomForestClassifier
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from sklearn.tree import DecisionTreeClassifier
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# Build paths inside the project like this: BASE_DIR / 'subdir'.
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BASE_DIR = Path(__file__).resolve().parent.parent
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@ -256,14 +257,29 @@ CELERY_RESULT_BACKEND = 'redis://localhost:6379/1'
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CELERY_ACCEPT_CONTENT = ['json']
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CELERY_TASK_SERIALIZER = 'json'
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DEFAULT_MODELS_PARAMS = {
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'base_clf': RandomForestClassifier(n_estimators=100,
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max_features='log2',
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random_state=42,
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criterion='entropy',
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ccp_alpha=0.0,
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max_depth=3,
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min_samples_leaf=1),
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DEFAULT_RF_MODEL_PARAMS = {
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'base_clf': RandomForestClassifier(
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n_estimators=100,
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max_features='log2',
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random_state=42,
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criterion='entropy',
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ccp_alpha=0.0,
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max_depth=3,
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min_samples_leaf=1
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),
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'num_chains': 10,
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}
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DEFAULT_DT_MODEL_PARAMS = {
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'base_clf': DecisionTreeClassifier(
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criterion='entropy',
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max_depth=3,
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min_samples_split=5,
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min_samples_leaf=5,
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max_features='sqrt',
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class_weight='balanced',
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random_state=42
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),
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'num_chains': 10,
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}
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