Enrichment Procedures for Soft Clusters: A Statistical Test and its Applications

Clusters, typically mined by modeling locality of attribute spaces, are often evaluated for their ability to demonstrate ‘enrichment’ of categorical features. A cluster enrichment procedure evaluates the membership of a cluster for significant representation in pre-defined categories of interest. While classical enrichment procedures assume a hard clustering definition, in this paper we introduce a new statistical test that computes enrichments for soft clusters. We demonstrate an application of this test in refining and evaluating soft clusters for classification of remotely sensed images

A survey of outlier detection methodologies

Outlier detection has been used for centuries to detect and, where appropriate, remove anomalous observations from data. Outliers arise due to mechanical faults, changes in system behaviour, fraudulent behaviour, human error, instrument error or simply through natural deviations in populations. Their detection can identify system faults and fraud before they escalate with potentially catastrophic consequences. It can identify errors and remove their contaminating effect on the data set and as such to purify the data for processing. The original outlier detection methods were arbitrary but now, principled and systematic techniques are used, drawn from the full gamut of Computer Science and Statistics. In this paper, we introduce a survey of contemporary techniques for outlier detection. We identify their respective motivations and distinguish their advantages and disadvantages in a comparative review

ASSESSING THE IMPORTANCE OF APPLE ATTRIBUTES: AN AGRICULTURAL APPLICATION OF CONJOINT ANALYSIS

The use of conjoint analysis in assessing consumers' preferences for attributes is demonstrated with the apple as an example. Conjoint analysis may be used to estimate the importance of attributes and attribute levels through decomposition of consumers' ranking of alternative attribute combinations. It is shown that conjoint analysis provides results that may not be obtained from a survey where respondents are asked to directly state their assessment of the importance of attributes.Food Consumption/Nutrition/Food Safety,