
https://colab.research.google.com/drive/16rmsJTBelh2vIWVxt9ncFEJmU7cEdUsE?usp=sharing

# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 744222727
- CO2 Emissions (in grams): 0.00509303545772981

## Validation Metrics

- Loss: 0.40596098709549455
- Accuracy: 0.8378378378378378
- Precision: 0.8518518518518519
- Recall: 0.92
- AUC: 0.8866666666666667
- F1: 0.8846153846153846

## Usage

```python
import json
import joblib

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

features = config['features']

# data = pd.read_csv("data.csv")
data = data[features]

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

```
{"tags": ["autotrain", "tabular", "classification", "structured-data-classification"], "datasets": ["vabadeh213/autotrain-data-titanic"], "co2_eq_emissions": 0.00509303545772981}
transformers joblib xgboost autotrain tabular classification structured-data-classification dataset:vabadeh213/autotrain-data-titanic co2_eq_emissions endpoints_compatible region:us
TAGS
#transformers #joblib #xgboost #autotrain #tabular #classification #structured-data-classification #dataset-vabadeh213/autotrain-data-titanic #co2_eq_emissions #endpoints_compatible #region-us 


URL

# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 744222727
- CO2 Emissions (in grams): 0.00509303545772981

## Validation Metrics

- Loss: 0.40596098709549455
- Accuracy: 0.8378378378378378
- Precision: 0.8518518518518519
- Recall: 0.92
- AUC: 0.8866666666666667
- F1: 0.8846153846153846

## Usage


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 744222727
- CO2 Emissions (in grams): 0.00509303545772981 ## Validation Metrics

- Loss: 0.40596098709549455
- Accuracy: 0.8378378378378378
- Precision: 0.8518518518518519
- Recall: 0.92
- AUC: 0.8866666666666667
- F1: 0.8846153846153846 ## Usage
TAGS
#transformers #joblib #xgboost #autotrain #tabular #classification #structured-data-classification #dataset-vabadeh213/autotrain-data-titanic #co2_eq_emissions #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 744222727
- CO2 Emissions (in grams): 0.00509303545772981 ## Validation Metrics

- Loss: 0.40596098709549455
- Accuracy: 0.8378378378378378
- Precision: 0.8518518518518519
- Recall: 0.92
- AUC: 0.8866666666666667
- F1: 0.8846153846153846 ## Usage
passage: TAGS
#transformers #joblib #xgboost #autotrain #tabular #classification #structured-data-classification #dataset-vabadeh213/autotrain-data-titanic #co2_eq_emissions #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 744222727
- CO2 Emissions (in grams): 0.00509303545772981## Validation Metrics

- Loss: 0.40596098709549455
- Accuracy: 0.8378378378378378
- Precision: 0.8518518518518519
- Recall: 0.92
- AUC: 0.8866666666666667
- F1: 0.8846153846153846## Usage