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
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file py4knn-0.0.5.tar.gz.
File metadata
- Download URL: py4knn-0.0.5.tar.gz
- Upload date:
- Size: 2.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.49.0 CPython/3.8.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
91c1cf5d9c016d85357a8522d032f012bbba52d89e6831caa85fcc8c3be516d5
|
|
| MD5 |
9d91e89dd994a2fa23e61a77871c34b9
|
|
| BLAKE2b-256 |
d31f92ef9b4d0aa8ff057e3aac14358292abdee0cfe70dea75e3ded1470d002b
|
File details
Details for the file py4knn-0.0.5-py3-none-any.whl.
File metadata
- Download URL: py4knn-0.0.5-py3-none-any.whl
- Upload date:
- Size: 2.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.49.0 CPython/3.8.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
173539824784c97dbf46aa7e90cf800c2c7001d2a59e28b5715518b60f370160
|
|
| MD5 |
17d63aca8b805e41b885d111c91d73df
|
|
| BLAKE2b-256 |
35527a5399069c1341ba0f964f177d6099ceee5e3c50c2569be7633dc4e82f09
|