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Model description

This is a linear regression model trained on California housing dataset. This model could be used to predict median price of a house in California, given certain features. This model is very basic and should only be used as an example of how to use Highwind.

Intended uses & limitations

This model is made for the purposes of showing how to use Highwind only.

Training Procedure

[More Information Needed]

Hyperparameters

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Hyperparameter Value
alpha 0.01
copy_X True
fit_intercept True
max_iter 1000
positive False
precompute False
random_state 42
selection cyclic
tol 0.0001
warm_start False

Model Plot

Lasso(alpha=0.01, random_state=42)
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Evaluation Results

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How to Get Started with the Model

import joblib
from huggingface_hub import hf_hub_download

# Feature scaler
hf_hub_download("MelioAI/california-housing", "scaler.joblib")
scaler = joblib.load("scaler.joblib")

# Classifier model
hf_hub_download("MelioAI/california-housing", "model.joblib")
model = joblib.load("model.joblib")

Model Card Authors

MelioAI, ruanmelio

Model Card Contact

You can contact the model card authors through following channels: [More Information Needed]

Citation

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BibTeX:

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Intended uses & limitations

This model is made for the purposes of showing how to use Highwind only.

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