autotrain tabular regression tabular-regression finance not-for-all-audiences chemistry biology legal music code medical climate art doi:10.57967/hf/1085 region:us
---
tags:
- autotrain
- tabular
- regression
- tabular-regression
- finance
- not-for-all-audiences
- chemistry
- biology
- legal
- music
- code
- medical
- climate
- art
datasets:
- Admin08077/autotrain-data-uis
co2_eq_emissions:
  emissions: 19.0283639884588
---

# Model Trained Using AutoTrain

- Problem type: Single Column Regression
- Model ID: 82843142547
- CO2 Emissions (in grams): 19.0284

## Validation Metrics

- Loss: 0.033
- R2: 0.790
- MSE: 0.001
- MAE: 0.015
- RMSLE: 0.029

## 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)

```