Initial changes to the features dataframe
Browse files
app.py
CHANGED
@@ -1,5 +1,6 @@
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import streamlit as st
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import joblib
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import numpy as np
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import xgboost
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# from sklearn.ensemble import GradientBoostingClassifier
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@@ -90,6 +91,18 @@ if uploaded_file is not None:
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features = feature_extraction.scale(features_list)
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# st.write(features)
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# Reshape the features to match the expected shape for prediction
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reshaped_features = features.reshape(1, -1)
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if model_name == "XGB - (Multi Label)":
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@@ -135,5 +148,4 @@ if uploaded_file is not None:
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st.write("No genre predicted above the threshold.")
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else:
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predicted_label = model.predict(features)[0]
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-
st.write(f"Predicted Genre: {predicted_label}")
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st.metric("Predicted Genre:",str(predicted_label))
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import streamlit as st
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import joblib
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import pandas as pd
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import numpy as np
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import xgboost
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# from sklearn.ensemble import GradientBoostingClassifier
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features = feature_extraction.scale(features_list)
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# st.write(features)
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# Features Dataframe
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df = pd.DataFrame({
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"fname": ["Feature -1", "Feature - 2"]
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})
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st.dataframe(
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df,
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column_config={
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"name": "Features"
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}
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)
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# Reshape the features to match the expected shape for prediction
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reshaped_features = features.reshape(1, -1)
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if model_name == "XGB - (Multi Label)":
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st.write("No genre predicted above the threshold.")
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else:
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predicted_label = model.predict(features)[0]
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st.metric("Predicted Genre:",str(predicted_label))
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