Customer relations -- Management -- Data processing; Self-organizing maps; Data mining
This study outlines a method of determining individual customer potential, based solely on data present in the customer database: descriptive information and transaction records. We define potential as the incremental turnover that any particular...
Data mining; SAS (Computer program language); Fuzzy algorithms
Clustering is the process of placing data records into homogenous groups. Members of each group are similar to one another and highly different from members outside the group. The clusters are used for predictive analysis (what will happen), for...
Discrimination in housing -- Connecticut -- New Haven; Housing -- Connecticut -- New Haven; African Americans -- Housing -- Connecticut -- New Haven
From the mid-1950s to the present, social scientists have produced an everincreasing
number of discourses on the topic of the concentration of urban poverty in the
United States. Although broad agreement exists on the effects of urban property,...
Fenway Park (Boston, Mass.); Baseball--Records.; Boston (Mass.)--Climate.
"Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in Data Mining."; Thesis advisor: Daniel Larose.; M.S.,Central Connecticut State University,,2013.; Includes bibliographical references (leaves 76-78).
Multivariate analysis; Stratified sets; Bayesian statistical decision theory
Data mining, at times, involves applying cluster analysis to large databases
containing multivariate normal parameters. Most finite mixture clustering methods use
the expectation-maximum (EM) algorithm to find solutions to the unknown parameters,...