sailu4/fuelcast-model

FuelCast Regression Model

This model predicts Consumer_Total_MomentaryFuel from ship, propulsion, and weather variables from the FuelCast dataset.

Training

• Dataset: krohnedigital/FuelCast
• Config: cps_poseidon
• Model: random_forest
• Rows used: 30000
• Target: Consumer_Total_MomentaryFuel

Metrics

Metric	Value
R2	0.9957
RMSE	0.0295
MAE	0.0194

Files

• fuelcast_model.joblib: complete scikit-learn pipeline
• metrics.json: evaluation metrics
• input_schema.json: expected raw input columns
• sample_input.json: example input row
• feature_importances.csv: feature importance when available

Usage

from huggingface_hub import hf_hub_download
import joblib
import pandas as pd

model_path = hf_hub_download(
    repo_id="username/fuelcast-model",
    filename="fuelcast_model.joblib",
)
model = joblib.load(model_path)

sample = pd.DataFrame([{"Ship_SpeedOverGround": 12.4}])
prediction = model.predict(sample)