Sarah Coppock

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Data mining partitioning is performed on attributes to increase data concentration. To choose effective partitioning attributes, a rough set based technique that measures the crispiness of the partitioning is presented. This technique is based on the mathematical theory of rough sets. This method is a simple and efficient approach to measure the crispiness(More)
Bacterial plasmids containing cDNA sequences specific for keratins were constructed from mRNA of cultured human epidermal cells. Two separate classes of cloned cDNAs were identified by positive hybrid selection: one class removed from total human epidermal mRNA a fraction that was translated into 56 and 58 kilodalton (kd) keratins, and the other class(More)
Clustering groups items together that are most similar to each other and sets those that are least similar into different clusters. Methods have been developed to cluster records in a data set that are of only qualitative or quantitative data. Data sets exist that contain a mix of qualitative (nominal and ordinal) and quantitative (discrete and continuous)(More)
Clustering groups records that are similar to each other into the same group, and those that are less similar into different groups. Clustering data of mixed types is difficult due to different data characteristics. Extending Gower’s metric for nominal and ordinal data is incorporated into an agglomerative hierarchical clustering algorithm to cluster mixed(More)
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