#!/usr/bin/env python
# coding: utf-8

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# install pycaret
# pip install pycaret

# pip install pycaret[full]


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from pycaret.utils import version
version()


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from pycaret.datasets import get_data
data = get_data('anomaly')


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data.describe().transpose()


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type(data)


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data.shape


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from pycaret.anomaly import *
s = setup(data, session_id = 123, log_experiment = True, experiment_name = 'anomaly-demo')


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models()


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iforest = create_model('iforest')


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iforest


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iforest = create_model('iforest', n_estimators=200)
iforest


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knn = create_model('knn')
print(knn)


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plot_model(iforest, plot = 'umap')


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save_model(iforest, model_name = 'abc')


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l = load_model('abc')


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from pycaret.anomaly import load_model, predict_model
l = load_model('iforest-abc', platform = 'aws', authentication = .......)
p = predict_model(l, data=data)
p.head()


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p


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iforest = create_model('iforest', fraction = 0.05)
results = assign_model(iforest)
results.head()


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results['Anomaly_Score'].hist(bins=100, figsize=(10,6))


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from sklearn import set_config
set_config(display=None)


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l


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deploy_model(iforest, 'iforest-abc', platform = 'aws', 
             authentication = {'bucket' : 'pycaret-test'})


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iforest


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type(iforest)


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results = assign_model(iforest)
results.head()


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