
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 53980126976
- CO2 Emissions (in grams): 0.9262

## Validation Metrics

- Loss: 0.459
- Accuracy: 0.773
- Precision: 0.667
- Recall: 0.704
- AUC: 0.852
- F1: 0.685

## Usage

```python
import json
import joblib
import pandas as pd

model = joblib.load('model.joblib')
config = json.load(open('config.json'))

features = config['features']

# data = pd.read_csv("data.csv")
data = data[features]
data.columns = ["feat_" + str(col) for col in data.columns]

predictions = model.predict(data)  # or model.predict_proba(data)

```
{"tags": ["autotrain", "tabular", "classification", "tabular-classification"], "datasets": ["M-Ahmad-Abid/autotrain-data-diabetes"], "co2_eq_emissions": {"emissions": 0.9261659630175969}}
transformers joblib xgboost autotrain tabular classification tabular-classification dataset:M-Ahmad-Abid/autotrain-data-diabetes co2_eq_emissions endpoints_compatible has_space region:us
TAGS
#transformers #joblib #xgboost #autotrain #tabular #classification #tabular-classification #dataset-M-Ahmad-Abid/autotrain-data-diabetes #co2_eq_emissions #endpoints_compatible #has_space #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 53980126976
- CO2 Emissions (in grams): 0.9262

## Validation Metrics

- Loss: 0.459
- Accuracy: 0.773
- Precision: 0.667
- Recall: 0.704
- AUC: 0.852
- F1: 0.685

## Usage


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 53980126976
- CO2 Emissions (in grams): 0.9262 ## Validation Metrics

- Loss: 0.459
- Accuracy: 0.773
- Precision: 0.667
- Recall: 0.704
- AUC: 0.852
- F1: 0.685 ## Usage
TAGS
#transformers #joblib #xgboost #autotrain #tabular #classification #tabular-classification #dataset-M-Ahmad-Abid/autotrain-data-diabetes #co2_eq_emissions #endpoints_compatible #has_space #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 53980126976
- CO2 Emissions (in grams): 0.9262 ## Validation Metrics

- Loss: 0.459
- Accuracy: 0.773
- Precision: 0.667
- Recall: 0.704
- AUC: 0.852
- F1: 0.685 ## Usage
TAGS
#transformers #joblib #xgboost #autotrain #tabular #classification #tabular-classification #dataset-M-Ahmad-Abid/autotrain-data-diabetes #co2_eq_emissions #endpoints_compatible #has_space #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 53980126976
- CO2 Emissions (in grams): 0.9262## Validation Metrics

- Loss: 0.459
- Accuracy: 0.773
- Precision: 0.667
- Recall: 0.704
- AUC: 0.852
- F1: 0.685## Usage