metadata
tags:
- autotrain
- tabular
- regression
- tabular-regression
datasets:
- vyver7952/autotrain-data-foreign-exchange-idr-usd
co2_eq_emissions:
emissions: 10.739693543319872
Model Trained Using AutoTrain
- Problem type: Single Column Regression
- Model ID: 50442120505
- CO2 Emissions (in grams): 10.7397
Validation Metrics
- Loss: 12.001
- R2: 1.000
- MSE: 144.031
- MAE: 5.758
- RMSLE: 0.001
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)