
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 934630783
- CO2 Emissions (in grams): 38.42484725553464

## Validation Metrics

- Loss: 0.2984429822985684
- Accuracy: 0.8628221244500315
- Precision: 0.7873263888888888
- Recall: 0.5908794788273616
- AUC: 0.9182195921357326
- F1: 0.6751023446222553

## 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": ["rajistics/autotrain-data-Adult"], "co2_eq_emissions": 38.42484725553464}
transformers joblib extra_trees autotrain tabular classification tabular-classification dataset:rajistics/autotrain-data-Adult co2_eq_emissions endpoints_compatible region:us
TAGS
#transformers #joblib #extra_trees #autotrain #tabular #classification #tabular-classification #dataset-rajistics/autotrain-data-Adult #co2_eq_emissions #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 934630783
- CO2 Emissions (in grams): 38.42484725553464

## Validation Metrics

- Loss: 0.2984429822985684
- Accuracy: 0.8628221244500315
- Precision: 0.7873263888888888
- Recall: 0.5908794788273616
- AUC: 0.9182195921357326
- F1: 0.6751023446222553

## Usage


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 934630783
- CO2 Emissions (in grams): 38.42484725553464 ## Validation Metrics

- Loss: 0.2984429822985684
- Accuracy: 0.8628221244500315
- Precision: 0.7873263888888888
- Recall: 0.5908794788273616
- AUC: 0.9182195921357326
- F1: 0.6751023446222553 ## Usage
TAGS
#transformers #joblib #extra_trees #autotrain #tabular #classification #tabular-classification #dataset-rajistics/autotrain-data-Adult #co2_eq_emissions #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 934630783
- CO2 Emissions (in grams): 38.42484725553464 ## Validation Metrics

- Loss: 0.2984429822985684
- Accuracy: 0.8628221244500315
- Precision: 0.7873263888888888
- Recall: 0.5908794788273616
- AUC: 0.9182195921357326
- F1: 0.6751023446222553 ## Usage
passage: TAGS
#transformers #joblib #extra_trees #autotrain #tabular #classification #tabular-classification #dataset-rajistics/autotrain-data-Adult #co2_eq_emissions #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 934630783
- CO2 Emissions (in grams): 38.42484725553464## Validation Metrics

- Loss: 0.2984429822985684
- Accuracy: 0.8628221244500315
- Precision: 0.7873263888888888
- Recall: 0.5908794788273616
- AUC: 0.9182195921357326
- F1: 0.6751023446222553## Usage