数据挖掘之Apriori算法详解和Python实现代码分享

2019-10-05 14:37:29丽君

#-*- encoding: UTF-8 -*-
#---------------------------------import------------------------------------
#---------------------------------------------------------------------------
class Apriori(object):

    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: