https://github.com/billsioros/classifier2d

2D Pattern Classification via Linear Programming for presentation purposes only
https://github.com/billsioros/classifier2d

classification classification-algorithm classifier linear-programming presentation python python3

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2D Pattern Classification via Linear Programming for presentation purposes only

• Host: GitHub
• URL: https://github.com/billsioros/classifier2d
• Owner: billsioros
• License: mit
• Created: 2020-01-25T12:32:57.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2023-12-15T14:42:06.000Z (over 2 years ago)
• Last Synced: 2025-01-24T22:46:35.528Z (over 1 year ago)
• Topics: classification, classification-algorithm, classifier, linear-programming, presentation, python, python3
• Language: Python
• Homepage:
• Size: 340 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 3
• Metadata Files:
  • Readme: README.md

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README

          
# 2D Pattern Classification via Linear Programming

![alt text](img/linearly_separable_example_no_guides.png)

## Set Up

    python -m venv env

    pip install -r requirements.txt

## Example Usage

    python classify.py -l 2 3 -g -e 20 -f ./img/example_usage

![alt text](img/example_usage.png)

## Available Options

    usage: classify.py [-h] [-g] [-r] [-f FIGURE] [-s SEED] [-n NUMBER] [-e EXTRA]

                    [-p PERCENTAGE] [-x AXIS [AXIS ...]] [-l LINE [LINE ...]]

                    [-d DISTANCE [DISTANCE ...]] [-c CLASSES [CLASSES ...]]

    2D Pattern Classification via Linear Programming

    optional arguments:

    -h, --help            show this help message and exit

    -g, --guides          draw guides connecting each point to the separation

                            line (default: False)

    -r, --random          generate the points completely at random (default:

                            False)

    -f FIGURE, --figure FIGURE

                            save the figure as a '.eps' file with the given

                            basename (default: None)

    -s SEED, --seed SEED  initialize the internal state of the random number

                            generator (default: None)

    -n NUMBER, --number NUMBER

                            specify the number of random points that make up the

                            training set (default: 100)

    -e EXTRA, --extra EXTRA

                            specify the number of random points that make up the

                            testing set (default: 0)

    -p PERCENTAGE, --percentage PERCENTAGE

                            specify the percentage of points belonging to the

                            first class (default: 0.5)

    -x AXIS [AXIS ...], --axis AXIS [AXIS ...]

                            specify the lower and upper bounds of the horizontal

                            axis (default: [-25.0, 25.0])

    -l LINE [LINE ...], --line LINE [LINE ...]

                            specify the slope and the y-intercept of the

                            separation line (default: [2.0, -3.0])

    -d DISTANCE [DISTANCE ...], --distance DISTANCE [DISTANCE ...]

                            specify the lower and upper bounds of the distance

                            from the separation line (default: [10.0, 80.0])

    -c CLASSES [CLASSES ...], --classes CLASSES [CLASSES ...]

                            specify the classes' labels (default: ['Negative',

                            'Positive'])