초록 ▼

A data processing and analysis system, and a method of using the same, for discovering implicit relationships in data. The method is executed in a computer system capable of receiving input data comprised of expert knowledge, empirical data, and user-defined constraints for any application domain. T

A data processing and analysis system, and a method of using the same, for discovering implicit relationships in data. The method is executed in a computer system capable of receiving input data comprised of expert knowledge, empirical data, and user-defined constraints for any application domain. The system and method provide any pre-processing the input data may require, and perform feature selection and extraction on the input data. Further, the system and method generate a graphical representation of the implicit relationships in the input data, indicating relationships between both class variables and feature variables. Also generated is a classifier that provides a semantic and statistical justification of its classification results which further provides: statistical relevancy of the data set, including an indication of the undersampled regions of the data space; a data analysis specific to a desired level of confidence; and a sound decision theoretical foundation for classification thresholding. The system and method generate a classifier capable of classifying a sample with respect to any variable, handle missing data values, and provide a complete data analysis.

대표청구항 ▼

1. A data processing and analysis system for discovering implicit relationships in data, comprising:means for inputting empirical data, expert domain knowledge, domain conditions, and sample data; a computing means for receiving the empirical data and expert domain knowledge from the means for input

1. A data processing and analysis system for discovering implicit relationships in data, comprising:means for inputting empirical data, expert domain knowledge, domain conditions, and sample data; a computing means for receiving the empirical data and expert domain knowledge from the means for inputting empirical data, the computing means having a memory means connected to a processing means, wherein the processing means stores the empirical data and expert domain knowledge in the memory means, pre-processes the empirical data and expert domain knowledge, selects and extracts features from the empirical data and expert-domain knowledge, generates correlation matrices, derives conditional probability tables, calculates posterior probabilities, creates a domain model, incorporating any user-defined domain conditions, for storage in the memory means, provides an output signal representative of the domain, and provides an output signal representing a classification of the sample data; and means for receiving the output signal representative of the domain and the output signal representing the classification of the sample data, for graphically displaying the representation of the domain, and for displaying the classification of the sample data.