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...
The online DVD rental company Netflix® advertises that their service "is the best way to
rent movies1." Though Netflix® claims they enable customers to "find and discover movies they
will enjoy", consistently renting movies that meet personal...
In this thesis, support vector machines, neural networks, logistic regression, naïve Bayes, classification and regression trees, the C5.0 algorithms, QUEST, CHAID and discriminant analysis have been implemented on nine real-world datasets. The...
Investor community and stock market watch companies' earnings report closely as earnings report is the most essential fundamental barometer of how financially healthy a company is. All public companies announce earnings every quarter, and the stock...
Data mining; Semiconductors -- Design and construction
Finding equipment causes of faulty devices in semiconductor manufacturing is inhibited by several difficulties which are briefly described. The main problem area focused on here is that of biased data mining methods. By judiciously selecting two...
Hospitals -- Emergency services -- Utilization; Children -- Health and hygiene
Emergency department care and primary care are ideally distinct parts of the health care delivery system. In theory, each answers a specific and different health care need. However, in practice this distinction blurs. Many visits to hospital...
With the rules and regulations the federal government has put in place, financial institutions must consistently improve their anti-money laundering programs. Financial institutions use alert monitoring systems to combat a number of money...
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,...
