def __init__(self, filename, min_support, item_start, item_end):         self.filename = filename         self.min_support = min_support # 最小支持度         self.min_confidence = 50         self.line_num = 0 # item的行数         self.item_start = item_start #  取哪行的item         self.item_end = item_end

        self.location = [[i] for i in range(self.item_end - self.item_start + 1)]         self.support = self.sut(self.location)         self.num = list(sorted(set([j for i in self.location for j in i])))# 记录item

        self.pre_support = [] # 保存前一个support,location,num         self.pre_location = []         self.pre_num = []

        self.item_name = [] # 项目名         self.find_item_name()         self.loop()         self.confidence_sup()

    def deal_line(self, line):         "提取出需要的项"         return [i.strip() for i in line.split(' ') if i][self.item_start - 1:self.item_end]

    def find_item_name(self):         "根据第一行抽取item_name"         with open(self.filename, 'r') as F:             for index,line in enumerate(F.readlines()):                 if index == 0:                     self.item_name = self.deal_line(line)                     break

    def sut(self, location):         """         输入[[1,2,3],[2,3,4],[1,3,5]...]         输出每个位置集的support [123,435,234...]         """         with open(self.filename, 'r') as F:             support = [0] * len(location)             for index,line in enumerate(F.readlines()):                 if index == 0: continue                 # 提取每信息                 item_line = self.deal_line(line)                 for index_num,i in enumerate(location):                     flag = 0                     for j in i:                         if item_line[j] != 'T':                             flag = 1                             break                     if not flag:                         support[index_num] += 1             self.line_num = index # 一共多少行,出去第一行的item_name         return support

    def select(self, c):         "返回位置"         stack = []         for i in self.location:             for j in self.num:                 if j in i:                     if len(i) == c:                         stack.append(i)                 else:                     stack.append([j] + i)         # 多重列表去重         import itertools         s = sorted([sorted(i) for i in stack])         location = list(s for s,_ in itertools.groupby(s))         return location

    def del_location(self, support, location):         "清除不满足条件的候选集"         # 小于最小支持度的剔除         for index,i in enumerate(support):             if i < self.line_num * self.min_support / 100:                 support[index] = 0         # apriori第二条规则,剔除         for index,j in enumerate(location):             sub_location = [j[:index_loc] + j[index_loc+1:]for index_loc in range(len(j))]             flag = 0             for k in sub_location:                 if k not in self.location:                     flag = 1                     break             if flag:                 support[index] = 0         # 删除没用的位置         location = [i for i,j in zip(location,support) if j != 0]         support = [i for i in support if i != 0]         return support, location

    def loop(self):         "s级频繁项级的迭代"         s = 2         while True:             print '-'*80             print 'The' ,s - 1,'loop'             print 'location' , self.location             print 'support' , self.support             print 'num' , self.num             print '-'*80

            # 生成下一级候选集             location = self.select(s)             support = self.sut(location)             support, location = self.del_location(support, location)             num = list(sorted(set([j for i in location for j in i])))             s += 1             if  location and support and num:                 self.pre_num = self.num                 self.pre_location = self.location                 self.pre_support = self.support

                self.num = num                 self.location = location                 self.support = support             else:                 break

    def confidence_sup(self):         "计算confidence"         if sum(self.pre_support) == 0:             print 'min_support error' # 第一次迭代即失败         else:             for index_location,each_location in enumerate(self.location):                 del_num = [each_location[:index] + each_location[index+1:] for index in range(len(each_location))] # 生成上一级频繁项级                 del_num = [i for i in del_num if i in self.pre_location] # 删除不存在上一级频繁项级子集                 del_support = [self.pre_support[self.pre_location.index(i)] for i in del_num if i in self.pre_location] # 从上一级支持度查找                 # print del_num                 # print self.support[index_location]                 # print del_support                 for index,i in enumerate(del_num): # 计算每个关联规则支持度和自信度                     index_support = 0                     if len(self.support) != 1:                         index_support = index                     support =  float(self.support[index_location])/self.line_num * 100 # 支持度                     s = [j for index_item,j in enumerate(self.item_name) if index_item in i]                     if del_support[index]:                         confidence = float(self.support[index_location])/del_support[index] * 100                         if confidence > self.min_confidence:                             print ','.join(s) , '->>' , self.item_name[each_location[index]] , ' min_support: ' , str(support) + '%' , ' min_confidence:' , str(confidence) + '%'

def main():     c = Apriori('basket.txt', 14, 3, 13)     d = Apriori('simple.txt', 50, 2, 6)

if __name__ == '__main__':     main() ############################################################################ Status API Training Shop Blog About © 2014 GitHub, Inc. Terms Privacy Security Contact