Storing outlier probabilities
Continue building the ensemble by writing the code block that loops over estimators and generates outlier probabilities.
The scaled apple dataset with extra features is available.
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Anomaly Detection in Python
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estimators = [IForest(n_estimators=50), IForest(n_estimators=100)]
shape = (len(apple), len(estimators))
probability_scores = np.empty(shape=shape)
for ____, ____ in ____:
# Fit the estimator
____