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# AutoTrain Dataset for project: sample-diabetes-predict |
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## Dataset Descritpion |
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This dataset has been automatically processed by AutoTrain for project sample-diabetes-predict. |
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### Languages |
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The BCP-47 code for the dataset's language is unk. |
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## Dataset Structure |
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### Data Instances |
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A sample from this dataset looks as follows: |
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```json |
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[ |
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{ |
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"target": 0, |
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"feat_HighBP": 0.0, |
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"feat_HighChol": 0.0, |
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"feat_CholCheck": 1.0, |
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"feat_BMI": 34.0, |
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"feat_Smoker": 1.0, |
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"feat_Stroke": 0.0, |
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"feat_HeartDiseaseorAttack": 0.0, |
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"feat_PhysActivity": 1.0, |
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"feat_Fruits": 1.0, |
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"feat_Veggies": 1.0, |
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"feat_HvyAlcoholConsump": 0.0, |
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"feat_AnyHealthcare": 1.0, |
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"feat_NoDocbcCost": 0.0, |
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"feat_GenHlth": 3.0, |
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"feat_MentHlth": 0.0, |
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"feat_PhysHlth": 0.0, |
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"feat_DiffWalk": 0.0, |
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"feat_Sex": 0.0, |
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"feat_Age": 6.0, |
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"feat_Education": 6.0, |
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"feat_Income": 7.0 |
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}, |
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{ |
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"target": 1, |
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"feat_HighBP": 0.0, |
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"feat_HighChol": 0.0, |
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"feat_CholCheck": 1.0, |
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"feat_BMI": 46.0, |
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"feat_Smoker": 1.0, |
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"feat_Stroke": 0.0, |
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"feat_HeartDiseaseorAttack": 0.0, |
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"feat_PhysActivity": 1.0, |
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"feat_Fruits": 1.0, |
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"feat_Veggies": 1.0, |
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"feat_HvyAlcoholConsump": 0.0, |
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"feat_AnyHealthcare": 1.0, |
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"feat_NoDocbcCost": 0.0, |
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"feat_GenHlth": 2.0, |
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"feat_MentHlth": 1.0, |
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"feat_PhysHlth": 0.0, |
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"feat_DiffWalk": 0.0, |
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"feat_Sex": 1.0, |
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"feat_Age": 10.0, |
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"feat_Education": 6.0, |
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"feat_Income": 5.0 |
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} |
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] |
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``` |
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### Dataset Fields |
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The dataset has the following fields (also called "features"): |
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```json |
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{ |
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"target": "ClassLabel(num_classes=2, names=['0.0', '1.0'], id=None)", |
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"feat_HighBP": "Value(dtype='float64', id=None)", |
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"feat_HighChol": "Value(dtype='float64', id=None)", |
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"feat_CholCheck": "Value(dtype='float64', id=None)", |
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"feat_BMI": "Value(dtype='float64', id=None)", |
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"feat_Smoker": "Value(dtype='float64', id=None)", |
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"feat_Stroke": "Value(dtype='float64', id=None)", |
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"feat_HeartDiseaseorAttack": "Value(dtype='float64', id=None)", |
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"feat_PhysActivity": "Value(dtype='float64', id=None)", |
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"feat_Fruits": "Value(dtype='float64', id=None)", |
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"feat_Veggies": "Value(dtype='float64', id=None)", |
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"feat_HvyAlcoholConsump": "Value(dtype='float64', id=None)", |
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"feat_AnyHealthcare": "Value(dtype='float64', id=None)", |
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"feat_NoDocbcCost": "Value(dtype='float64', id=None)", |
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"feat_GenHlth": "Value(dtype='float64', id=None)", |
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"feat_MentHlth": "Value(dtype='float64', id=None)", |
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"feat_PhysHlth": "Value(dtype='float64', id=None)", |
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"feat_DiffWalk": "Value(dtype='float64', id=None)", |
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"feat_Sex": "Value(dtype='float64', id=None)", |
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"feat_Age": "Value(dtype='float64', id=None)", |
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"feat_Education": "Value(dtype='float64', id=None)", |
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"feat_Income": "Value(dtype='float64', id=None)" |
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} |
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``` |
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### Dataset Splits |
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This dataset is split into a train and validation split. The split sizes are as follow: |
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| Split name | Num samples | |
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| ------------ | ------------------- | |
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| train | 56552 | |
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| valid | 14140 | |
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