No self-introduction
Loading
Profile
Follow
codes (1)
K-Medoids algorithm
4.0
#!/usr/bin/python
import argparse
import csv
import numpy
import sys
# SCRIPT PARAMETERS
parser = argparse.ArgumentParser(description='k-Medoids clustering implementation.')
parser.add_argument('--dataset', required=True, help='File in CSV format containing samples.')
parser.add_argument('--k', required=True, type=int, help='Number of clusters.')
parser.add_argument('--iterations', required=False, default=500, type=int, help='Maximum number of iterations.')
opt = vars(parser.parse_args())
# GLOBAL VARIABLES
targetClass = ''
attributeClass = {}
data = []
medoids = []
k = opt['k']
N = 0 # N: size of training set
max_iter = int(opt['iterations'])
# LOAD DATASET
with open(opt['dataset']) as f:
reader = csv.DictReader(f, delimiter='\t')
# LOAD ATTRIBUTE TYPES (continuous, discrete, ignore)
attributeClass = reader.next()
# DETERMINE TARGET CLASS
classLine = reader.next()
for i in attributeClass:
if classLine[i]=='class':
targetClass = i
sudheer_kaushik 0 0
1
No more~
Follows0
Fans0