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A machine learning model builded on python, using multiple linear regression to predict MPG consumption of vehicules.

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MPG_LR_model

A machine learning model builded on python, using multiple linear regression to predict MPG consumption of vehicules.

Created with Mohamed EL-ELIEM "med.eleliem@gmail.com"

Data-set source :

https://archive.ics.uci.edu/ml/machine-learning-databases/auto-mpg/

  1. Title: Auto-Mpg Data

  2. Sources: (a) Origin: This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University. The dataset was used in the 1983 American Statistical Association Exposition. (c) Date: July 7, 1993

  3. Past Usage:

    • See 2b (above)
    • Quinlan,R. (1993). Combining Instance-Based and Model-Based Learning. In Proceedings on the Tenth International Conference of Machine Learning, 236-243, University of Massachusetts, Amherst. Morgan Kaufmann.
  4. Relevant Information:

    This dataset is a slightly modified version of the dataset provided in the StatLib library. In line with the use by Ross Quinlan (1993) in predicting the attribute "mpg", 8 of the original instances were removed because they had unknown values for the "mpg" attribute. The original dataset is available in the file "auto-mpg.data-original".

    "The data concerns city-cycle fuel consumption in miles per gallon, to be predicted in terms of 3 multivalued discrete and 5 continuous attributes." (Quinlan, 1993)

  5. Number of Instances: 398

  6. Number of Attributes: 9 including the class attribute

  7. Attribute Information:

    1. mpg: continuous
    2. cylinders: multi-valued discrete
    3. displacement: continuous
    4. horsepower: continuous
    5. weight: continuous
    6. acceleration: continuous
    7. model year: multi-valued discrete
    8. origin: multi-valued discrete
    9. car name: string (unique for each instance)
  8. Missing Attribute Values: horsepower has 6 missing values

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A machine learning model builded on python, using multiple linear regression to predict MPG consumption of vehicules.

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