Apriori 内存不足
Apriori Not enough memory
我正在使用 R 并使用以下命令，但出现错误 not enough memory. Increase minimum support! 我尝试将支持增加到 0.5，但我仍然遇到相同的错误。任何帮助，将不胜感激。我的数据是 (5000,2).
> x=apriori(d,parameter = list(support=0.5,confidence=0.8,maxlen=5))
Apriori
Parameter specification:
confidence minval smax arem aval originalSupport maxtime support minlen maxlen target ext
0.8 0.1 1 none FALSE TRUE 5 0.3 1 5 rules FALSE
Algorithmic control:
filter tree heap memopt load sort verbose
0.1 TRUE TRUE FALSE TRUE 2 TRUE
Absolute minimum support count: 0
set item appearances ...[0 item(s)] done [0.00s].
set transactions ...[2856 item(s), 2 transaction(s)] done [0.00s].
sorting and recoding items ... [2856 item(s)] done [0.00s].
creating transaction tree ... done [0.00s].
checking subsets of size 1 2 3 done [183.38s].
writing ... Error in apriori(d, parameter = list(support = 0.3, confidence = 0.8, :
not enough memory. Increase minimum support!
In addition: Warning messages:
1: In asMethod(object) : removing duplicated items in transactions
2: In apriori(d, parameter = list(support = 0.3, confidence = 0.8, :
Mining stopped (time limit reached). Only patterns up to a length of 3 returned!
您需要超过 2 笔交易。关联规则挖掘通常用于数千笔交易。
我正在使用 R 并使用以下命令，但出现错误 not enough memory. Increase minimum support! 我尝试将支持增加到 0.5，但我仍然遇到相同的错误。任何帮助，将不胜感激。我的数据是 (5000,2).
> x=apriori(d,parameter = list(support=0.5,confidence=0.8,maxlen=5))
Apriori
Parameter specification:
confidence minval smax arem aval originalSupport maxtime support minlen maxlen target ext
0.8 0.1 1 none FALSE TRUE 5 0.3 1 5 rules FALSE
Algorithmic control:
filter tree heap memopt load sort verbose
0.1 TRUE TRUE FALSE TRUE 2 TRUE
Absolute minimum support count: 0
set item appearances ...[0 item(s)] done [0.00s].
set transactions ...[2856 item(s), 2 transaction(s)] done [0.00s].
sorting and recoding items ... [2856 item(s)] done [0.00s].
creating transaction tree ... done [0.00s].
checking subsets of size 1 2 3 done [183.38s].
writing ... Error in apriori(d, parameter = list(support = 0.3, confidence = 0.8, :
not enough memory. Increase minimum support!
In addition: Warning messages:
1: In asMethod(object) : removing duplicated items in transactions
2: In apriori(d, parameter = list(support = 0.3, confidence = 0.8, :
Mining stopped (time limit reached). Only patterns up to a length of 3 returned!
您需要超过 2 笔交易。关联规则挖掘通常用于数千笔交易。