metadata

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
      - 1
      - 0
    x5:
      - 0
      - 0
      - 0
    x6:
      - 0
      - 0
      - 0
    x7:
      - 0
      - 0
      - 1
    x8:
      - 0
      - 1
      - 0
    x9:
      - 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
normalize	deprecated
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.

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:

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