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Update app.py
Browse filesremoved CO2 tracking bc too heavy
app.py
CHANGED
@@ -17,12 +17,12 @@ from sklearn.model_selection import train_test_split, GridSearchCV
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from sklearn.tree import DecisionTreeClassifier,export_graphviz # Import Decision Tree Classifier
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import mlflow
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from sklearn import metrics
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from codecarbon import EmissionsTracker
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#%matplotlib inline
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# Initialize the emissions tracker
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tracker = EmissionsTracker()
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tracker.start()
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#st.set_page_config(layout='wide')
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st.set_option('deprecation.showPyplotGlobalUse', False)
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#####################################################################
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@@ -978,9 +978,9 @@ if selected == "Conclusion":
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Additionally, we could also merge our current dataset with other datasets that may provide additional insights. By incorporating external datasets, we can enhance the quality and accuracy of our model predictions.
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""")
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# Stop the emissions tracker
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emissions = tracker.stop()
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st.write(f"Total CO2 emissions:{emissions:.4f}kg CO2")
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from sklearn.tree import DecisionTreeClassifier,export_graphviz # Import Decision Tree Classifier
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import mlflow
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from sklearn import metrics
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#from codecarbon import EmissionsTracker
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#%matplotlib inline
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# Initialize the emissions tracker
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# tracker = EmissionsTracker()
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# tracker.start()
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#st.set_page_config(layout='wide')
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st.set_option('deprecation.showPyplotGlobalUse', False)
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#####################################################################
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Additionally, we could also merge our current dataset with other datasets that may provide additional insights. By incorporating external datasets, we can enhance the quality and accuracy of our model predictions.
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""")
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# # Stop the emissions tracker
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# emissions = tracker.stop()
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# st.write(f"Total CO2 emissions:{emissions:.4f}kg CO2")
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