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---
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
```
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