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strmlt.py
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strmlt.py
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import logging
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import numpy as np
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import numpy as np
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import pandas as pd
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import pandas as pd
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import sys
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import streamlit as st
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import streamlit as st
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import uncurl
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import uncurl
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from calibration import overconfidence
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from calibration import overconfidence
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@ -163,11 +165,24 @@ if __name__ == "__main__":
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# ---
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# ---
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for strategy in ['uniform', 'quantile']:
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for n_bins in range(1, 300):
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try:
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fig = plotly_calibration(y_true, y_pred, n_bins=n_bins, strategy=strategy)
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fig = plotly_calibration(y_true, y_pred, n_bins=n_bins, strategy=strategy)
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st.plotly_chart(fig, use_container_width=True)
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# st.plotly_chart(fig, use_container_width=True)
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fig = plotly_calibration_odds(y_true, y_pred, n_bins=n_bins, strategy=strategy)
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fig = plotly_calibration_odds(y_true, y_pred, n_bins=n_bins, strategy=strategy)
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st.plotly_chart(fig, use_container_width=True)
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# st.plotly_chart(fig, use_container_width=True)
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except:
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st.warning("Hey! Unfortunately, there occured a mysterious error, which I haven't been able to reproduce locally. Try refreshing the page or changing the number of bins a bit. <3")
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np.set_printoptions(threshold=sys.maxsize)
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logging.info("=" * 40)
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logging.info(f"n_bins={n_bins}, strategy={strategy}")
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logging.info(f"true={repr(y_true)}")
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logging.info(f"y_pred={repr(y_pred)}")
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logging.info("=" * 40)
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# overconf = overconfidence(y_true, y_pred)
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# overconf = overconfidence(y_true, y_pred)
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# st.write(f"Your over/under- confidence score is {overconf:.2f}.")
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# st.write(f"Your over/under- confidence score is {overconf:.2f}.")
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