readme: ---
  tags:
  - autotrain
  - tabular
  - classification
  - tabular-classification
  datasets:
  - reesu/autotrain-data-wine_quality
  co2_eq_emissions:
    emissions: 8.276808778335907
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 3195889861
  - CO2 Emissions (in grams): 8.2768
  
  ## Validation Metrics
  
  - Loss: 0.995
  - Accuracy: 0.569
  - Macro F1: 0.296
  - Micro F1: 0.569
  - Weighted F1: 0.543
  - Macro Precision: 0.447
  - Micro Precision: 0.569
  - Weighted Precision: 0.558
  - Macro Recall: 0.283
  - Micro Recall: 0.569
  - Weighted Recall: 0.569
  
  ## 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)
  
  ```