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Commit From AutoTrain

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  1. .gitattributes +3 -0
  2. README.md +51 -0
  3. config.json +1 -0
  4. model.joblib +3 -0
.gitattributes CHANGED
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  *.zip 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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+ tokenizer.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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+ - ketong3906/autotrain-data-iris_truncated
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+ co2_eq_emissions:
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+ emissions: 0.9776538031455683
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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: 64451135750
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+ - CO2 Emissions (in grams): 0.9777
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.091
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+ - Accuracy: 1.000
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+ - Macro F1: 1.000
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+ - Micro F1: 1.000
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+ - Weighted F1: 1.000
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+ - Macro Precision: 1.000
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+ - Micro Precision: 1.000
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+ - Weighted Precision: 1.000
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+ - Macro Recall: 1.000
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+ - Micro Recall: 1.000
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+ - Weighted Recall: 1.000
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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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+ ```
config.json ADDED
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+ {"features": ["sepal_length", "sepal_width", "petal_length", "petal_width"], "targets": ["target"], "model_type": "xgboost", "target_mapping": {"setosa": 0, "versicolor": 1, "virginica": 2}}
model.joblib ADDED
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+ oid sha256:4e8ae8373c2700c3888f97e485a162a17f124570a2cc413dda2dce5c0dae0809
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+ size 169049