Hey everyone,
I just started learning R and statistics. I made association rules with the
apriori algorithm in the arules package. I sorted them and pruned them. But now
I want to validate/test them. In supervised learning they use cross validation.
In this paper by Patrick O Perry http://arxiv.org/abs/0909.3052 I read it is
possible to use cross validation on unsupervised learning methods (such as
arules). But since my background in R, statistics and machine learning is weak
the paper was quite hard to get through (also I'm not in college, I just
finished high school and am preparing to study computer sciencec).
So my question is, how do you validate your rules? How can you use cross
validation to do so? I have my main data set "Orders", it has 2 million
records. I used the sample function to make a training data set and a test data
set. But what do I do next? Are there other techniques I should know of?
If there are any specific tutorials on this subject, I would also love to learn
from them.
Kind regards,
Ayane
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