search
HomeBackend DevelopmentPython TutorialPython聚类算法之DBSACN实例分析

本文实例讲述了Python聚类算法之DBSACN。分享给大家供大家参考,具体如下:

DBSCAN:是一种简单的,基于密度的聚类算法。本次实现中,DBSCAN使用了基于中心的方法。在基于中心的方法中,每个数据点的密度通过对以该点为中心以边长为2*EPs的网格(邻域)内的其他数据点的个数来度量。根据数据点的密度分为三类点:

核心点:该点在邻域内的密度超过给定的阀值MinPs。
边界点:该点不是核心点,但是其邻域内包含至少一个核心点。
噪音点:不是核心点,也不是边界点。

有了以上对数据点的划分,聚合可以这样进行:各个核心点与其邻域内的所有核心点放在同一个簇中,把边界点跟其邻域内的某个核心点放在同一个簇中。

# scoding=utf-8
import pylab as pl
from collections import defaultdict,Counter
points = [[int(eachpoint.split("#")[0]), int(eachpoint.split("#")[1])] for eachpoint in open("points","r")]
# 计算每个数据点相邻的数据点,邻域定义为以该点为中心以边长为2*EPs的网格
Eps = 10
surroundPoints = defaultdict(list)
for idx1,point1 in enumerate(points):
  for idx2,point2 in enumerate(points):
    if (idx1 < idx2):
      if(abs(point1[0]-point2[0])<=Eps and abs(point1[1]-point2[1])<=Eps):
        surroundPoints[idx1].append(idx2)
        surroundPoints[idx2].append(idx1)
# 定义邻域内相邻的数据点的个数大于4的为核心点
MinPts = 5
corePointIdx = [pointIdx for pointIdx,surPointIdxs in surroundPoints.iteritems() if len(surPointIdxs)>=MinPts]
# 邻域内包含某个核心点的非核心点,定义为边界点
borderPointIdx = []
for pointIdx,surPointIdxs in surroundPoints.iteritems():
  if (pointIdx not in corePointIdx):
    for onesurPointIdx in surPointIdxs:
      if onesurPointIdx in corePointIdx:
        borderPointIdx.append(pointIdx)
        break
# 噪音点既不是边界点也不是核心点
noisePointIdx = [pointIdx for pointIdx in range(len(points)) if pointIdx not in corePointIdx and pointIdx not in borderPointIdx]
corePoint = [points[pointIdx] for pointIdx in corePointIdx] 
borderPoint = [points[pointIdx] for pointIdx in borderPointIdx]
noisePoint = [points[pointIdx] for pointIdx in noisePointIdx]
# pl.plot([eachpoint[0] for eachpoint in corePoint], [eachpoint[1] for eachpoint in corePoint], 'or')
# pl.plot([eachpoint[0] for eachpoint in borderPoint], [eachpoint[1] for eachpoint in borderPoint], 'oy')
# pl.plot([eachpoint[0] for eachpoint in noisePoint], [eachpoint[1] for eachpoint in noisePoint], 'ok')
groups = [idx for idx in range(len(points))]
# 各个核心点与其邻域内的所有核心点放在同一个簇中
for pointidx,surroundIdxs in surroundPoints.iteritems():
  for oneSurroundIdx in surroundIdxs:
    if (pointidx in corePointIdx and oneSurroundIdx in corePointIdx and pointidx < oneSurroundIdx):
      for idx in range(len(groups)):
        if groups[idx] == groups[oneSurroundIdx]:
          groups[idx] = groups[pointidx]
# 边界点跟其邻域内的某个核心点放在同一个簇中
for pointidx,surroundIdxs in surroundPoints.iteritems():
  for oneSurroundIdx in surroundIdxs:
    if (pointidx in borderPointIdx and oneSurroundIdx in corePointIdx):
      groups[pointidx] = groups[oneSurroundIdx]
      break
# 取簇规模最大的5个簇
wantGroupNum = 3
finalGroup = Counter(groups).most_common(3)
finalGroup = [onecount[0] for onecount in finalGroup]
group1 = [points[idx] for idx in xrange(len(points)) if groups[idx]==finalGroup[0]]
group2 = [points[idx] for idx in xrange(len(points)) if groups[idx]==finalGroup[1]]
group3 = [points[idx] for idx in xrange(len(points)) if groups[idx]==finalGroup[2]]
pl.plot([eachpoint[0] for eachpoint in group1], [eachpoint[1] for eachpoint in group1], 'or')
pl.plot([eachpoint[0] for eachpoint in group2], [eachpoint[1] for eachpoint in group2], 'oy')
pl.plot([eachpoint[0] for eachpoint in group3], [eachpoint[1] for eachpoint in group3], 'og')
# 打印噪音点,黑色
pl.plot([eachpoint[0] for eachpoint in noisePoint], [eachpoint[1] for eachpoint in noisePoint], 'ok')  
pl.show()

运行效果截图如下:

希望本文所述对大家Python程序设计有所帮助。

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
详细讲解Python之Seaborn(数据可视化)详细讲解Python之Seaborn(数据可视化)Apr 21, 2022 pm 06:08 PM

本篇文章给大家带来了关于Python的相关知识,其中主要介绍了关于Seaborn的相关问题,包括了数据可视化处理的散点图、折线图、条形图等等内容,下面一起来看一下,希望对大家有帮助。

详细了解Python进程池与进程锁详细了解Python进程池与进程锁May 10, 2022 pm 06:11 PM

本篇文章给大家带来了关于Python的相关知识,其中主要介绍了关于进程池与进程锁的相关问题,包括进程池的创建模块,进程池函数等等内容,下面一起来看一下,希望对大家有帮助。

Python自动化实践之筛选简历Python自动化实践之筛选简历Jun 07, 2022 pm 06:59 PM

本篇文章给大家带来了关于Python的相关知识,其中主要介绍了关于简历筛选的相关问题,包括了定义 ReadDoc 类用以读取 word 文件以及定义 search_word 函数用以筛选的相关内容,下面一起来看一下,希望对大家有帮助。

归纳总结Python标准库归纳总结Python标准库May 03, 2022 am 09:00 AM

本篇文章给大家带来了关于Python的相关知识,其中主要介绍了关于标准库总结的相关问题,下面一起来看一下,希望对大家有帮助。

分享10款高效的VSCode插件,总有一款能够惊艳到你!!分享10款高效的VSCode插件,总有一款能够惊艳到你!!Mar 09, 2021 am 10:15 AM

VS Code的确是一款非常热门、有强大用户基础的一款开发工具。本文给大家介绍一下10款高效、好用的插件,能够让原本单薄的VS Code如虎添翼,开发效率顿时提升到一个新的阶段。

Python数据类型详解之字符串、数字Python数据类型详解之字符串、数字Apr 27, 2022 pm 07:27 PM

本篇文章给大家带来了关于Python的相关知识,其中主要介绍了关于数据类型之字符串、数字的相关问题,下面一起来看一下,希望对大家有帮助。

详细介绍python的numpy模块详细介绍python的numpy模块May 19, 2022 am 11:43 AM

本篇文章给大家带来了关于Python的相关知识,其中主要介绍了关于numpy模块的相关问题,Numpy是Numerical Python extensions的缩写,字面意思是Python数值计算扩展,下面一起来看一下,希望对大家有帮助。

python中文是什么意思python中文是什么意思Jun 24, 2019 pm 02:22 PM

pythn的中文意思是巨蟒、蟒蛇。1989年圣诞节期间,Guido van Rossum在家闲的没事干,为了跟朋友庆祝圣诞节,决定发明一种全新的脚本语言。他很喜欢一个肥皂剧叫Monty Python,所以便把这门语言叫做python。

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

Repo: How To Revive Teammates
1 months agoBy尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
2 weeks agoBy尊渡假赌尊渡假赌尊渡假赌
Hello Kitty Island Adventure: How To Get Giant Seeds
1 months agoBy尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools

MinGW - Minimalist GNU for Windows

MinGW - Minimalist GNU for Windows

This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

MantisBT

MantisBT

Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

Atom editor mac version download

Atom editor mac version download

The most popular open source editor

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor