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Commit From AutoTrain

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  1. .gitattributes +3 -0
  2. README.md +51 -0
  3. config.json +3 -0
  4. model.joblib +3 -0
.gitattributes CHANGED
@@ -32,3 +32,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.bin.* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.gz filter=lfs diff=lfs merge=lfs -text
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+ *.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ tags:
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+ - autotrain
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+ - tabular
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+ - classification
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+ - tabular-classification
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+ datasets:
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+ - navidfk/autotrain-data-wine
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+ co2_eq_emissions:
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+ emissions: 23.98337622177028
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+ ---
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+
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+ # Model Trained Using AutoTrain
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+
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+ - Problem type: Multi-class Classification
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+ - Model ID: 1986366196
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+ - CO2 Emissions (in grams): 23.9834
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.792
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+ - Accuracy: 0.705
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+ - Macro F1: 0.345
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+ - Micro F1: 0.705
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+ - Weighted F1: 0.683
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+ - Macro Precision: 0.365
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+ - Micro Precision: 0.705
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+ - Weighted Precision: 0.676
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+ - Macro Recall: 0.341
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+ - Micro Recall: 0.705
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+ - Weighted Recall: 0.705
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+
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+ ## Usage
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+
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+ ```python
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+ import json
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+ import joblib
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+ import pandas as pd
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+
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+ model = joblib.load('model.joblib')
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+ config = json.load(open('config.json'))
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+
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+ features = config['features']
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+
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+ # data = pd.read_csv("data.csv")
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+ data = data[features]
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+ data.columns = ["feat_" + str(col) for col in data.columns]
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+
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+ predictions = model.predict(data) # or model.predict_proba(data)
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+
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+ ```
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