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

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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