Meiliu Lu

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The object of this paper is to introduce our development experience of a data mining system for prospective real estate sellers and buyers to determine properties price. The prediction of continuous values of properties selling prices is modeled by a statistical technique called predictive regression. The prerequisite of this data mining process is to(More)
Making a class schedule for next semester that suits a student's interests and meets overall graduation requirements within a time frame is not always easy. The changing requirements, transferable units of different schools, the availability of classes and other factors can often cause mistakes in the scheduling process. An automated tool can help students(More)
In this paper, we describe our study on enrollment prediction using support vector machines and rule-based predictive models. The goal is to predict the total enrollment headcount that is composed of new (freshman and transfer), continued and returned students. The proposed approach builds predictive models for new, continued and returned students,(More)
Vital statistics data offer a fertile ground for data mining. In this paper, we discuss the results of a data mining project on the causes of death aspect of the vital statistics data in the state of California. A data mining tool called Cubist is used to build predictive models out of two million cases over a nine-year period. The objective of our study is(More)
In our previous work, we described a framework called i<sup>2</sup>Learning for a perpetual learning agent to be engaged in continuous learning to incrementally improve its problem solving performance over time. i<sup>2</sup>Learning offers an overarching framework that can accommodate various inconsistency-specific learning strategies. In this paper, we(More)
One of the long-term research questions in machine learning is how to build never-ending learners. The state-of-the-practice in the field of machine learning thus far is still dominated by the one-time learner paradigm: some learning algorithms are utilized on data sets to produce certain results, and then the learner is put away and the results are put to(More)
Search engines of today do a great job of sifting through billions of pages of Internet content and returning search results highly relevant to user queries. However, in localized implementations (a local university search or an Intranet search of a private company), the same search engine technology usually has less than satisfactory performance. The(More)