--- library_name: sklearn tags: - sklearn - skops - tabular-regression model_file: linreg.pkl widget: structuredData: x0: - -0.3839236795902252 - -0.9788183569908142 - 1.0937178134918213 x1: - -0.5319488644599915 - -1.108436107635498 - 0.9354732036590576 x2: - -0.38279563188552856 - -1.3128694295883179 - 1.4773520231246948 x3: - 0.2815782427787781 - -0.11783809214830399 - -0.9529813528060913 x4: - 1.0 - 1.0 - 0.0 x5: - 0.0 - 0.0 - 0.0 x6: - 0.0 - 0.0 - 0.0 x7: - 0.0 - 0.0 - 1.0 x8: - 0.0 - 1.0 - 0.0 x9: - 0.0 - 0.0 - 0.0 --- # Model description This is a regression model on MPG dataset trained. ## Intended uses & limitations This model is not ready to be used in production. ## Training Procedure ### Hyperparameters The model is trained with below hyperparameters.
Click to expand | Hyperparameter | Value | |------------------|---------| | copy_X | True | | fit_intercept | True | | n_jobs | | | positive | False |
### Model Plot The model plot is below.
LinearRegression()
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## Evaluation Results You can find the details about evaluation process and the evaluation results. | Metric | Value | |--------------------|----------| | Mean Squared Error | 5.01069 | | R-Squared | 0.883503 | # How to Get Started with the Model Use the code below to get started with the model. ```python import joblib import json import pandas as pd clf = joblib.load(linreg.pkl) 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: [More Information Needed] # 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:** ``` [More Information Needed] ```