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License: Apache License 2.0
In the examples, I notice that the iris dataset is not split into train and test.
Is cross validation performed by default? Can you please shed some light on this?
The final data frame is not type consistent. Numeric columns, confidence, support and lift, have the char type. It is problem if I want to sort data after pruning (I have to transform columns to numeric explicitly).
After pruning, the Lift column contains only zero values.
When I was trying to use the sample code of fpgrowth function, it does not work. The error message is:
Error in fpgrowth(train = txns, support = 0.03, confidence = 0.03, minlen = 2, :
unused argument (minlen = 2)
It looks like that the frameToRules function sometimes returns error "invalid class “itemMatrix” object: item labels not unique"
Some debugging showed that
unique(unlist(sapply(rowItems, function(x) x$ant)))
does not filter out repeating items.
A fix seems to be replacing this with
unique(c(unlist(sapply(rowItems, function(x) x$ant))))
That is
antItems <- unique(c(unlist(sapply(rowItems, function(x) x$ant))))
consItems <- unique(c(unlist(sapply(rowItems, function(x) x$cons))))
I am trying to fit a fpgrowth model on a in-built data set called Adult. While fitting a model, I was getting an error as shown below.
Error in .jcall(jPruning, "[[Ljava/lang/String;", "fpgrowth", support, :
method fpgrowth with signature (DDI)[[Ljava/lang/String; not found
I used the below R code to fit fpgrowth model.
library(rCBA)
data("Adult")
Adult<-as(Adult,"transactions")
rules = rCBA::fpgrowth(Adult, support=0.001, confidence=0.5, maxLength=2)
What's wrong with the above code?
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