python自写DBSCAN算法
- python3.x
- matplotlib
- numpy
Step 1. Download this repository with git or click the download ZIP button
$ git clone https://github.com/guoswang/DBSACN_Example.git
$ cd DBSACN_Example
Step 2. run DBSACN_Example.py
$ python DBSACN_Example.py
数据集是周志华《机器学习》中的西瓜数据集4.0
0.697,0.46
0.774,0.376
0.634,0.264
0.608,0.318
0.556,0.215
0.403,0.237
0.481,0.149
0.437,0.211
0.666,0.091
0.243,0.267
0.245,0.057
0.343,0.099
0.639,0.161
0.657,0.198
0.36,0.37
0.593,0.042
0.719,0.103
0.359,0.188
0.339,0.241
0.282,0.257
0.748,0.232
0.714,0.346
0.483,0.312
0.478,0.437
0.525,0.369
0.751,0.489
0.532,0.472
0.473,0.376
0.725,0.445
0.446,0.459
def loadDataSet(filename):
dataSet = []
fr = open(filename)
for line in fr.readlines():
curLine = line.strip().split(',')
fltLine = map(float, curLine)
#python2.x map函数返回list
#dataSet.append(fltLine)
#python3.x map函数返回迭代器
dataSet.append(list(fltLine))
return dataSet
def draw(C , dataSet):
color = ['r', 'y', 'g', 'b', 'c', 'k', 'm']
for i in C.keys():
X = []
Y = []
datas = C[i]
for j in range(len(datas)):
X.append(dataSet[datas[j]][0])
Y.append(dataSet[datas[j]][1])
plt.scatter(X, Y, marker='o', color=color[i % len(color)], label=i)
plt.legend(loc='upper right')
plt.show()
def main():
dataSet = loadDataSet("dataSet.txt")
print(dataSet)
C = DBSCAN(dataSet, 0.11, 5)
draw(C, dataSet)
if __name__ == '__main__':
main()
