moro23/used-phones-price-prediction

Model description

This model is a regression model that predicts the price of a used phones

Intended uses & limitations

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Training Procedure

Hyperparameters

The model is trained with below hyperparameters.

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Hyperparameter	Value
alpha	0.0001
copy_X	True
fit_intercept	True
max_iter
normalize	deprecated
positive	False
random_state
solver	auto
tol	0.001

Model Plot

The model plot is below.

Ridge(alpha=0.0001)

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Evaluation Results

You can find the details about evaluation process and the evaluation results.

Metric	Value

How to Get Started with the Model

Use the code below to get started with the model.

import joblib
import json
import pandas as pd
clf = joblib.load(price-prediction-model.bin)
with open("config.json") as f:
    config = json.load(f)
clf.predict(pd.DataFrame.from_dict(config["sklearn"]["example_input"]))

Model Card Authors

This model card is written by following authors:

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Model Card Contact

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

Citation

Below you can find information related to citation.

BibTeX:

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