Reproducible KNN

The KNN algorithm is written in src/knn.py. All functions have documentation that guides the user on how to use the code. However, we offer a command line interface to ease the usage of the model.

Dependencies

As a Python application, you can use the requirements.txt file to install the application's dependencies:

$ pip install -r requirements.txt

Usage

We have the following available methods in the command line:

• evaluate

How to check the method usage

To check how to use a specific method, you can run:

$ python main.py <method> -h

This will show you the mandatory and optional parameters as well a description of the method. For example:

$ python main.py evaluate -h

NAME
    main.py evaluate - Evaluate a model using the specified dataset and changing its parameters. We use k-fold cross validation repeated 5 times as the evaluation method. The results are saved in the results/<dataset>.csv

SYNOPSIS
    main.py evaluate DATASET <flags>

DESCRIPTION
    Evaluate a model using the specified dataset and changing its parameters. We use k-fold cross validation repeated 5 times as the evaluation method. The results are saved in the results/<dataset>.csv

POSITIONAL ARGUMENTS
    DATASET
        Type: str
        (str) Name of the dataset to be used.
        Possible values: ['iris', 'letter', 'mushroom', 'dis', 'shuttle', 'adult', 'breast_cancer', 'lupus', 'spambase']

FLAGS
    --seed=SEED
        Type: int
        Default: 1234
        (int, default 1234) Seed for random state.

NOTES
    You can also use flags syntax for POSITIONAL ARGUMENTS

For example:

$ python main.py evaluate iris