k Nearest Neighbor Classifier Algorithm Implementation

Required Packages:

- numpy
- scikit-learn (for testing)

Usage:

Imports

from sklearn.datasets import load_iris
from k_nearest_neighbors import k_nearest_neighbors

Test data:

iris = load_iris()
data = iris.data
target = iris.target

Model:

# Instantiate model
classifier = k_nearest_neighbors(n_neighbors=10)

# Fit
classifier.fit_knn(data, target)

# Prediction
classifier.predict_knn([[1,2,3,4,5,6,7,8,9,10]])

# Nearest neighbors and euclidean distance (specified in n_neighbors)
classifier.display_knn([[1,2,3,4,5,6,7,8,9,10]])