fishknn

K 최근접 이웃 알고리즘
어떤 데이터에 대한 답을 구할 때 
주위의 다른 데이터들(K)의 근접 거리(이웃범위)를 계산하여
다수를 차지하는 것을 정답으로 예측

배경

파이썬 ML scikit-learn 의 sklearn.neighbors.KNeighborsClassifier 모듈을 이용해 미리 학습된 모델을 이용해 분류(class) 예측이 가능 함을 살펴보았습니다.

프로그램 동작 방식

학습된 모델이 없는 상태에서 출발합니다.
사용자는 길이, 무게 데이터를 처음 입력하고 프로그램을 예측 값을 출력합니다 (도미, 빙어) 이때 프로그램을 학습 데이터가 없어 임의의 값을 예측합니다.
사용자는 예측값의 정답 유무를 다시 입력합니다. ( 이때 프로그램을 예측 이후 정답인지 사용자에게 묻게 됩니다 )
위의 과정을 반복하며 프로그램을 입력된 데이터(훈련데이터)와 정답(타켓) 데이터를 저장하고 있고 입력이 반복 되면 계속 모델을 진화 시켜 나갑니다.

Usage

$ predictor
🐟 물고기의 길이를 입력하세요 (cm): 18.5
🐟 물고기의 무게를 입력하세요  (g): 16
🐟 이 물고기는 빙어입니다.
🐟 예측이 맞습니까? (y/n): y
🐟 예측 성공🥳

Metadata

Release files for seokxkyu_fishknn 1.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for seokxkyu_fishknn 1.0.1
File	Size	Uploaded	Provenance	Actions
seokxkyu_fishknn-1.0.1.tar.gz	3.0 kB	Sep 9, 2024	Without provenance	Details for seokxkyu_fishknn-1.0.1.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for seokxkyu_fishknn 1.0.1
File	Interpreter	ABI	Platform	Actions Reset
seokxkyu_fishknn-1.0.1-py3-none-any.whl 3.6 kB Sep 9, 2024 Without provenance	Python 3	none	any	Details for seokxkyu_fishknn-1.0.1-py3-none-any.whl

Total release size: 6.6 kB

Release files / seokxkyu_fishknn-1.0.1.tar.gz

Download URL	seokxkyu_fishknn-1.0.1.tar.gz
Size	3.0 kB
Tags	Source
SHA-256 checksum How to use checksums	`c74a87164905dcbda2e880f6a7522c60992e9f1ab55f83e82b6cc97cb81c4a5b`
BLAKE2b-256 checksum How to use checksums	`df2a5d1c0ead5b55cb565553b30f0dc773adf06a1806f8060f943fd3ccc200c3`
Upload date	Sep 9, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`pdm/2.17.1 CPython/3.12.4 Linux/5.15.153.1-microsoft-standard-WSL2`

Release files / seokxkyu_fishknn-1.0.1-py3-none-any.whl

Download URL	seokxkyu_fishknn-1.0.1-py3-none-any.whl
Size	3.6 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`8115ea083c19687f4da77f01b4d7c680faa2350e42c93e3cb7f5522ce928c60c`
BLAKE2b-256 checksum How to use checksums	`c437ab9fb55cf9cc354eda929f321507cdb1b63af45b616e65a5bac19a185793`
Upload date	Sep 9, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`pdm/2.17.1 CPython/3.12.4 Linux/5.15.153.1-microsoft-standard-WSL2`

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This release

1.0.1 This release

Sep 9, 2024 2 release files No provenance

1.0.0