---
tags:
- autotrain
- tabular
- regression
- tabular-regression
datasets:
- rea-knn/autotrain-data
---

# Model Trained Using AutoTrain

- Problem type: Tabular regression

## Validation Metrics

- r2: 0.4161997019836754
- mse: 1507403520.3284101
- mae: 29120.68408236499
- rmse: 38825.29485178973
- rmsle: 0.18675257705362744
- loss: 38825.29485178973

## Best Params

- n_neighbors: 3
- weights: distance
- algorithm: ball_tree
- leaf_size: 77
- p: 2
- metric: manhattan

## 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]

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

# predictions can be converted to original labels using label_encoders.pkl

```