问题描述
所以我有此表：
Trans_ID Name Fuzzy_Value Total_Item
100 I1 0.33333333 3
100 I2 0.33333333 3
100 I5 0.33333333 3
200 I2 0.5 2
200 I5 0.5 2
300 I2 0.5 2
300 I3 0.5 2
400 I1 0.33333333 3
400 I2 0.33333333 3
400 I4 0.33333333 3
500 I1 0.5 2
500 I3 0.5 2
600 I2 0.5 2
600 I3 0.5 2
700 I1 0.5 2
700 I3 0.5 2
800 I1 0.25 4
800 I2 0.25 4
800 I3 0.25 4
800 I5 0.25 4
900 I1 0.33333333 3
900 I2 0.33333333 3
900 I3 0.33333333 3
1000 I1 0.2 5
1000 I2 0.2 5
1000 I4 0.2 5
1000 I6 0.2 5
1000 I8 0.2 5
和2个空白表：
Table ITEMSET
"ITEM_SET" "Support"
Table Confidence
"ANTECEDENT" "CONSEQUENT"
我需要为每次交易中出现的每个项目找到FUZZY值：
I need to find FUZZY value for each item that occur in each transaction:
I1 = Sum of (Fuzzy_Value from item I1 in trans 100 until 1000 which is trans: 100,400,500,700,800,900,1000)/Total Trans
-> (.33333333+0.33333333+0.5+0.5+0.25+0.33333333+0.2)/10 = 0.244999999
I2 = Sum of (Fuzzy_Value from item I2 in trans 100 - 1000 which is trans:100,200,300,400,600,800,900,1000)/Total Trans
-> (0.33333333+0.5+0.5+0.33333333+0.5+0.25+0.33333333)/10 = 0.274999999
I3 -> 0.258333333
I4 -> 0.103333333
I5 -> 0.058333333
I6 -> 0.02
I8 -> 0.02
例如：我使用最低支持10％-> 0.1
我需要删除I5，I6，I8，因为它的值< 0.1 => 修剪步骤
For EX: i use minimum Support 10% -> 0.1
I need to remove I5,I6,I8 since it's value < 0.1 => prune step
然后存储
I1=0.244999999, I2=0.274999999, I3=0.258333333,I4=0.103333333 on new table 'ITEMSET'
2组合
注意：这是之后的基本第一步这很可能需要使用重复或递归，因为该过程将一直进行下去，直到没有其他项目组合是不可能的为止。
然后从剩下的东西中我需要找到K + 1个项目集（即2个组合项集）=> 加入步骤
{I1,I2} =Sum of (Fuzzy_Value from item I1 + I2 in trans 100 - 1000 which is trans:100,400,800,900,1000)/Total Trans
->(0.666666667+0.666666667+0.5+0.666666667+0.4)/9 = 0.29
*do the same for the rest*
{I1,I3} =(1+1+0.5+0.666666667)/9 = 0.316666667
{I1,I4} =(0.666666667+0.4)/9 = 0.106666667
{I2,I3} =(1+1+0.5+0.666666667)/9 = 0.316666667
{I2,I4} =(1+0.666666667+0.4)/9 =0.206666667
{I3,I4} =0
然后执行另一个修剪步骤，删除小于0.1的值{I3，I4}
Then Do another Prune Step removing less than 0.1 value which is {I3,I4}
Store {I1,I2} = 0.29, {I1,I3} = 0.316666667, {I1,I4} =0.106666667, {I2,I3} = 0.316666667, {I2,I4} = 0.206666667 AT "ITEMSET" TABLE
3组合
此后，再次进行 JOIN STEP 合并通过修剪的项集
After that Do another JOIN STEP combining itemset that pass pruning
{I1,I2,I3} = Sum of (Fuzzy_Value from item I1 + I2 +I3 in trans 100 - 1000 which is trans:800,900)/Total Trans
-> 0.75+1 = 0.175
**Same for the rest**
{I1,I2,I4} = 1+0.6 = 0.16
{I2,I3,I4} = 0
执行另一个修剪步骤，删除小于0.1的值，即{I1，I3，I4 }
Do another Prune Step removing less than 0.1 value which is {I1,I3,I4}
Store {I1,I2,I3} = 0.176 AND {I1,I2,I4} = 0,16 AT "ITEMSET" TABLE
4个组合
通过修剪K + 4（4个组合）的组合项集
Combine itemset that pass pruning K+4 (4 combination)
{I1,I2,I3,I4} = 0
**因为没有包含该项目的交易
**since no transaction containing this item
在处理停止后，因为没有可能的组合了
after process stop since there's no possible combination left
此时ITEMSET数据库具有：
at this point ITEMSET database have :
ITEM_SET Support
{I1} 0.244999999
{I2} 0.274999999
{I3} 0.258333333
{I4} 0.103333333
{I1,I2} 0.29
{I1,I3} 0.316666667
{I1,I4} 0.106666667
{I2,I3} 0.316666667
{I2,I4} 0.206666667
{I1,I2,I3} 0.176
{I1,I2,I4} 0,16
如何在sql中编写代码？
非常感谢
how do i code that in sql?thank you very much
*注意：您可以根据需要添加另一个表
*note: you can add another table as needed
推荐答案
步骤1：
CREATE TABLE ITEMSET
SELECT Name, SUM(Fuzzy_Value)/COUNT(*) Fuzzy_Value
FROM trans
GROUP BY ID
HAVING ROUND(SUM(Fuzzy_Value), 1) >= 0.1
请注意 ROUND（）函数-这很重要，因为您有.33333之类的值不能求和
Note the ROUND() function - it's important, because you have values like .33333 that don't sum in a happy way.
步骤2：
ALTER TABLE ITEMSET ADD INDEX (Name)
SELECT a.Name Name1, b.Name Name2, SUM(Fuzzy_Value)/COUNT(*) Fuzzy_Value
FROM ITEMSET a JOIN ITEMSET b ON (a.Name != b.Name)
GROUP BY a.Name, b.Name
HAVING ROUND(SUM(Fuzzy_Value), 1) >= 0.1
Opps：我刚刚注意到您是在半年前问过的，所以我想继续下去是没有意义的。如果您仍然需要此答案，请发表评论。
Opps: I just noticed that you asked this half a year ago, so I guess there is no point in continuing. If you still need this answer leave a comment.
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