--- tags: - autotrain - tabular - classification - tabular-classification datasets: - navidfk/autotrain-data-wine co2_eq_emissions: emissions: 23.98337622177028 --- # Model Trained Using AutoTrain - Problem type: Multi-class Classification - Model ID: 1986366196 - CO2 Emissions (in grams): 23.9834 ## Validation Metrics - Loss: 0.792 - Accuracy: 0.705 - Macro F1: 0.345 - Micro F1: 0.705 - Weighted F1: 0.683 - Macro Precision: 0.365 - Micro Precision: 0.705 - Weighted Precision: 0.676 - Macro Recall: 0.341 - Micro Recall: 0.705 - Weighted Recall: 0.705 ## 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) ```