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Update app.py
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app.py
CHANGED
@@ -8,6 +8,12 @@ image = Image.open('pic2.jpg')
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st.image(image,caption = 'Network Data Anomaly',width =1000)
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st.title("Network Data Anomaly")
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with open("./median.pickle", 'rb') as f:
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MED = pickle.load(f)
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st.image(image,caption = 'Network Data Anomaly',width =1000)
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st.title("Network Data Anomaly")
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st.write("""An anomaly (also known as an outlier) is when something happens that is outside of the norm,
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when it stands out or deviates from what is expected. There are different kinds of anomalies in an e-commerce setting,
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they can be product anomaly, conversion anomaly or marketing anomaly.
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The model used is Isolation Forest, which is built based on decision trees and is an unsupervised model.
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Isolation forests can be used to detect anomaly in high dimensional and large datasets, with no labels.
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""")
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with open("./median.pickle", 'rb') as f:
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MED = pickle.load(f)
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