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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)
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)
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)
Data mining discouvers interesting information from a data set. Mining incorporates different methods and considers different kinds of information. Granulation is an important task of mining. Mining methods include: association rule discouvery, classification, partitioning, clustering, and sequence discouvery. The data sets can be extremely large with(More)
Similarity is important in knowledge discovery. Cluster analysis, classification, and granulation each involve some notion or definition of similarity. The measurement of similarity is selected based on the domain and distribution of the data. Even within a specific domain, some similarity metrics may be considered more useful than others. There is an(More)
The Preparing Future Faculty program we describe here was established in 1999 as part of the national PFF3 initiative. Originally based in one department in a college of engineering in a large midwestern state university, the program dramatically increased the number of students in our department opting for academic careers and has been expanded to serve(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)
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