This paper gives a survey of contrast set mining (CSM), emerging pattern mining (EPM), and subgroup discovery (SD) in a unifying framework named supervised descriptive rule discovery. The paper contributes a novel understanding of these sub-areas of data mining by presenting a unified terminology, by explaining the apparent differences between the learning tasks and by exploring the apparent differences between the approaches. The paper also provides a critical survey of existing supervised descriptive rule discovery visualization methods.
COBISS.SI-ID: 22475303
As a methodological novelty, we show that the contrast set mining problem can be effectively solved by transforming it to a more common and well-understood subgroup discovery task. We also show that the explanatory potential of discovered contrast sets can be improved by offering additional contrast set descriptors, called the supporting factors. The proposed methodology has been applied to data about two groups of patients, with ischemia caused by thrombosis and by embolism, respectively.
COBISS.SI-ID: 22479655
Many models of outcrossing between crops were developed, but most of them are mechanistic, very complex and rarely evaluated against real data. Our approach uses field measurements and background knowledge to develop accurate equation-based models of the outcrossing between GM and conventional maize fields. We have also analyzed the relative influence of climatic and geographic parameters on the outcrossing and tested the transferability of the equation-based models on different datasets.
COBISS.SI-ID: 22574375
Informal organizational structure established via a day-to-day communication between the employees reflects informal processes in an organization and in general can substantially differ from the formal organizational structure. Our approach is based on Semantic Technologies and analyzes an internal social network to propose an informal organizational structure. The output is a lightweight ontology. The approach is evaluated on the real-world data set of a mid-size organization.
COBISS.SI-ID: 22843175
With the application of multi-objective regression tree analysis we have determined underlying relationships between soil properties and its resistance and resilience capacity. Models with multiple dependent variables (multi-objective models) for the simultaneous prediction of interdependent resilience and resistance were used to procude maps of resilience characteristics of soils for Scotland.
COBISS.SI-ID: 22691623