Machine Learning and Small Data
Zhongmin Cui
Abstract
Abstract Commonly used machine learning applications seem to relate to big data. This article provides a gentle review of machine learning and shows why machine learning can be applied to small data too. An example of applying machine learning to screen irregularity reports is presented. In the example, the support vector machine and multinomial naïve Bayes methods were used and compared. The performance of machine learning was compared to human experts in terms of flagging records to be excluded from equating. The application of machine learning seemed to be successful, although the data only consisted of a couple of thousand records. Recommendations in using machine learning are provided.
Topics & Concepts
Machine learningArtificial intelligenceFlaggingComputer scienceSupport vector machineOnline machine learningNaive Bayes classifierComputational learning theoryEquatingActive learning (machine learning)MathematicsStatisticsArchaeologyHistoryRasch modelData Mining Algorithms and ApplicationsData Analysis with RAdvanced Text Analysis Techniques