K-Nearest Neighbors Python Library
Project description
py4knn
K-Nearest Neighbors Python Library
Getting Started
This project is simply an implementation of K-Nearest Neighbors algorithm in python programming language.
Prerequisites
This Project Has No Prerequisites
Installing
The easiest way to install py4knn is by using pip
pip install py4knn
Usage
There is only 1 public method of knn class. It is predict method, it takes 5 argument namely x_train
, t_train
, x_test
, k
, and distance
calculation method. We provide 6 distances namely euclidean, squared_euclidean, manhattan, canberra, chebyshev, and bray_curtis.
from py4knn.k_nearest_neighbors import knn
classifier = knn()
x_train = [[0.23,0.54],[0.45,1.23],[1.54,0.23],[0.93,0.535]]
t_train = [0,1,0,1]
x_test = [[0.34,0.65],[0.90,0.50]]
y = classifier.predict(x_train,t_train,x_test,1,'euclidean')
Project details
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