metadata
tags:
- autotrain
- tabular
- classification
- tabular-classification
datasets:
- dozata/autotrain-data-petfinder-demo
co2_eq_emissions:
emissions: 0.49257909869639516
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 87059143318
- CO2 Emissions (in grams): 0.4926
Validation Metrics
- Loss: 4.209
- Accuracy: 0.033
- Macro F1: 0.003
- Micro F1: 0.033
- Weighted F1: 0.010
- Macro Precision: 0.003
- Micro Precision: 0.033
- Weighted Precision: 0.008
- Macro Recall: 0.011
- Micro Recall: 0.033
- Weighted Recall: 0.033
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]
data.columns = ["feat_" + str(col) for col in data.columns]
predictions = model.predict(data) # or model.predict_proba(data)