v1.0.0

Iris Flowers Classification with k-Nearest Neighbors v1.0.0

This release introduces the first version of the Iris Flowers Classification package, implementing the k-Nearest Neighbors (k-NN) algorithm. The package allows you to classify Iris flowers into three species: setosa, versicolor, and virginica, based on four features: sepal length, sepal width, petal length, and petal width.

Features

• k-Nearest Neighbors Classifier: Train and predict using k-NN.
• Cross-Validation: Evaluate model performance with 5-fold cross-validation.
• Custom Input: Provide your own measurements for classification.
• Comprehensive Documentation: Includes class and sequence diagrams.

Installation

Install directly from PyPI:

pip install IrisKNNClassifier

Or, install from source:

pip install .

Running the Classifier

After installation, run the classifier directly:

iris-classifier

Screenshots

Here are some screenshots showcasing the program's functionality:

Program Interface

Prediction Result

Full Changelog

For a complete list of changes, see the Full Changelog.

Download

You can download the binaries here:

• IrisKNNClassifier-1.0.0-py3-none-any.whl
• IrisKNNClassifier-1.0.0.tar.gz

Or install directly from PyPI using pip:

pip install IrisKNNClassifier