[英]converting s4 object to data frame or list issue in r
我一直在嘗試在r中對數據庫執行apriori algorithm
。 當我這樣做時,我意識到apriori算法返回s4對象。 實際上,如果我不想將結果寫入數據庫,這不是問題。
我開始這樣寫我的r代碼; 首先,我加載與我的分析有關的軟件包
library(DBI)
library(rJava)
library(RJDBC)
library(Matrix)
library(grid)
library(arules)
library(arulesViz)
getwd()
setwd("D:/R")
getwd()
jdbcDriver<-JDBC(driverClass = "oracle.jdbc.OracleDriver",classPath = "D:/R/ojdbc6.jar")
jdbcConnection<-dbConnect(jdbcDriver,"jdbc:oracle:ip:port","user","pass")
ana_sorgu<- dbGetQuery(jdbcConnection,"SELECT action_id, product_cat FROM table")
urunler<-dbGetQuery(jdbcConnection,"select distinct product_cat from product_cat")
i <- split(ana_sorgu$PRODUCT_CAT,ana_sorgu$ACTION_ID)
txn <- as(i, "transactions")
sorgu2<-as.list(urunler$PRODUCT_CAT)
for(row2 in 1:nrow(urunler)) {
basket_rules<-apriori(data=txn, parameter=list(supp=0.001,conf = 0.4), appearance = list(default="lhs",rhs=sorgu2[[row2]]))
deneme<-inspect(basket_rules)#i guess that something has to be changed to write here releated to next for loop but i can't
for(row in 1:length(basket_rules)) {
jdbcDriver2<-JDBC(driverClass = "oracle.jdbc.OracleDriver",classPath = "D:/R/ojdbc6.jar", identifier.quote = "\"")
jdbcConnection2<-dbConnect(jdbcDriver,"jdbc:oracle:ip:port","user","pass")
sorgu <- paste0("insert into market_basket_analysis_3 (lhs,rhs,support,confidence,lift) values ('",deneme$lhs[[row]],"','",deneme$rhs[[row]],"','",deneme$support[[row]],"','",deneme$confidence[[row]],"','",deneme$lift[[row]],"')")
print(sorgu)
result<-dbSendUpdate(jdbcConnection2,sorgu)
dbDisconnect(jdbcConnection2)
}}
我創建了一個名為sorgu2的變量,以便按產品類別對產品類別進行動態分析,因此我在as.list()中實現了urunler $ PRODUCT_CAT。因此,我可以在循環中的rhs中使用它。
最后,當我執行此鱈魚時,它會返回;
Apriori
Parameter specification:
confidence minval smax arem aval originalSupport support minlen maxlen target ext
0.4 0.1 1 none FALSE TRUE 0.001 1 10 rules FALSE
Algorithmic control:
filter tree heap memopt load sort verbose
0.1 TRUE TRUE FALSE TRUE 2 TRUE
Absolute minimum support count: 854
set item appearances ...[1 item(s)] done [0.00s].
set transactions ...[793 item(s), 854614 transaction(s)] done [0.34s].
sorting and recoding items ... [350 item(s)] done [0.05s].
creating transaction tree ... done [0.99s].
checking subsets of size 1 2 3 4 done [0.20s].
writing ... [0 rule(s)] done [0.00s].
creating S4 object ... done [0.12s].
[1] "insert into market_basket_analysis_3 (lhs,rhs,support,confidence,lift) values ('','','','','')"
[1] "insert into market_basket_analysis_3 (lhs,rhs,support,confidence,lift) values ('','','','','')"
Apriori
Parameter specification:
confidence minval smax arem aval originalSupport support minlen maxlen target ext
0.4 0.1 1 none FALSE TRUE 0.001 1 10 rules FALSE
Algorithmic control:
filter tree heap memopt load sort verbose
0.1 TRUE TRUE FALSE TRUE 2 TRUE
Absolute minimum support count: 854
set item appearances ...[1 item(s)] done [0.00s].
set transactions ...[793 item(s), 854614 transaction(s)] done [0.33s].
sorting and recoding items ... [350 item(s)] done [0.05s].
creating transaction tree ... done [0.98s].
checking subsets of size 1 2 3 4 done [0.20s].
writing ... [0 rule(s)] done [0.00s].
creating S4 object ... done [0.12s].
[1] "insert into market_basket_analysis_3 (lhs,rhs,support,confidence,lift) values ('','','','','')"
[1] "insert into market_basket_analysis_3 (lhs,rhs,support,confidence,lift) values ('','','','','')"
Error in asMethod(object) :
NISASTA PATATES ALGR2 is an unknown item label
我在哪里做錯了? 提前致謝。
您可以使用unclass
來查看由arules
生成的S4對象的內容(僅顯示我稱為deneme
的對象的前5個元素,就像您的元素一樣,但顯然具有不同的內容):
> unclass(deneme[1:5])
<S4 Type Object>
attr(,"quality")
support confidence lift
4 0.0001528538 1.0 1362.9583
38 0.0001222830 1.0 1362.9583
27287 0.0001222830 0.8 872.2933
94270 0.0001222830 0.8 872.2933
226 0.0001222830 0.8 817.7750
attr(,"info")
attr(,"info")$data
msweb.trans
attr(,"info")$ntransactions
[1] 32711
attr(,"info")$support
[1] 1e-04
attr(,"info")$confidence
[1] 0.8
attr(,"lhs")
itemMatrix in sparse format with
5 rows (elements/transactions) and
284 columns (items)
attr(,"rhs")
itemMatrix in sparse format with
5 rows (elements/transactions) and
284 columns (items)
您可以使用attr
訪問每個attr
:
> attr(deneme[1:5], "quality")
support confidence lift
4 0.0001528538 1.0 1362.9583
38 0.0001222830 1.0 1362.9583
27287 0.0001222830 0.8 872.2933
94270 0.0001222830 0.8 872.2933
226 0.0001222830 0.8 817.7750
其中quality
是一個包含三列的數據框,則可以使用$
來訪問它們:
> attr(deneme[1:5], "quality")$confidence
[1] 1.0 1.0 0.8 0.8 0.8
盡管lhs
和rhs
是itemMatrix
對象,但是您可以使用inspect來獲取實際的項目,如下所示:
as(as(attr(deneme[1:5], "lhs"), "transactions"), "data.frame")$items
我想以此暗示,您可以修改代碼以插入數據庫; 如果您仍有疑問,請告訴我。
希望能幫助到你。
評論后編輯 :請勿使用
as(as(attr(basket_rules, "lhs"), "transactions"), "data.frame")$items[[row]]
但反而
as(as(attr(basket_rules[row], "lhs"), "transactions"), "data.frame")$items
您的最終代碼將如下所示:
for(row2 in 1:nrow(urunler)) {
basket_rules<-apriori(data=txn, parameter=list(supp=0.001,conf = 0.4), appearance = list(default="lhs",rhs=sorgu2[[row2]]))
for(row in 1:length(basket_rules)) {
jdbcDriver2<-JDBC(driverClass = "oracle.jdbc.OracleDriver",classPath = "D:/R/ojdbc6.jar", identifier.quote = "\"")
jdbcConnection2<-dbConnect(jdbcDriver,"jdbc:oracle:ip:port","user","pass")
sorgu <- paste0("insert into market_basket_analysis_3 (lhs,rhs,support,confidence,lift) values ('",as(as(attr(basket_rules[row], "lhs"), "transactions"), "data.frame")$items,"','",as(as(attr(basket_rules[row], "rhs"), "transactions"), "data.frame")$items,"','",attr(basket_rules[row],"quality")$support,"','",attr(basket_rules[row],"quality")$confidence,"','",attr(basket_rules[row],"quality")$lift,"')")
result<-dbSendUpdate(jdbcConnection2,sorgu)
dbDisconnect(jdbcConnection2)
}
}
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