51 citations · 60 across the 6 of their papers we have counts for
6 papers
Clustering students' open-ended questionnaire answers
Wilhelmiina Hämäläinen, Mike Joy, Florian Berger +1
Open responses form a rich but underused source of information in educational data mining and intelligent tutoring systems. One of the major obstacles is the difficulty of clusteri…
Specious rules: an efficient and effective unifying method for removing misleading and uninformative patterns in association rule mining
Wilhelmiina Hämäläinen, Geoffrey I. Webb
We present theoretical analysis and a suite of tests and procedures for addressing a broad class of redundant and misleading association rules we call \emph{specious rules}. Specio…
A Tutorial on Statistically Sound Pattern Discovery
Wilhelmiina Hämäläinen, Geoffrey I. Webb
Statistically sound pattern discovery harnesses the rigour of statistical hypothesis testing to overcome many of the issues that have hampered standard data mining approaches to pa…
Assessing the statistical significance of association rules
Wilhelmiina Hämäläinen
An association rule is statistically significant, if it has a small probability to occur by chance. It is well-known that the traditional frequency-confidence framework does not pr…
General upper bounds for well-behaving goodness measures on dependency rules
Wilhelmiina Hämäläinen
In the search for statistical dependency rules, a crucial task is to restrict the search space by estimating upper bounds for the goodness of yet undiscovered rules. In this paper,…
New tight approximations for Fisher's exact test
Wilhelmiina Hämäläinen
Fisher's exact test is often a preferred method to estimate the significance of statistical dependence. However, in large data sets the test is usually too worksome to be applied,…