transformers joblib xgboost autotrain tabular classification tabular-classification dataset:dozata/autotrain-data-petfinder-demo co2_eq_emissions endpoints_compatible region:us
---
tags:
- autotrain
- tabular
- classification
- tabular-classification
datasets:
- dozata/autotrain-data-petfinder-demo
co2_eq_emissions:
  emissions: 0.49257909869639516
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 87059143318
- CO2 Emissions (in grams): 0.4926

## Validation Metrics

- Loss: 4.209
- Accuracy: 0.033
- Macro F1: 0.003
- Micro F1: 0.033
- Weighted F1: 0.010
- Macro Precision: 0.003
- Micro Precision: 0.033
- Weighted Precision: 0.008
- Macro Recall: 0.011
- Micro Recall: 0.033
- Weighted Recall: 0.033

## 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)

```