Background Data measuring airborne pollutants, public health and environmental factors
are increasingly being stored and merged. These big datasets offer great potential, but also …

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 …

We present a novel algorithm for significant pattern mining, Westfall-Young light. The target
patterns are statistically significantly enriched in one of two classes of objects. Our method …

State-based or condition-based alarming has emerged as a prevalent method to reduce
nuisance alarms and inhibit alarm floods in the alarm management of process industries …

Statistical dependency analysis is the basis of all empirical science. A commonly occurring
problem is to find the most significant dependency rules, which describe either positive or …

Obtaining accurate class prediction of a query object is an important component of
supervised classification. However, it could be also important to understand the …

With the popularity of Web 2.0, there has been a phenomenal increase in the utility of text
classification in applications like document filtering and sentiment categorization. Many of …

Objective: Association rule mining is one of the data mining process for discovering frequent
item set between transaction databases. The main objective of this research work is …

Emerging pattern–based classification is an ongoing branch in Pattern Recognition.
However, despite its simplicity and accurate results, this classification includes an a priori …

Co-location rule mining is one of the tasks of spatial data mining, which focuses on the
detection of sets of spatial features that show spatial associations. Most previous methods …