Imputation of Missing Data in Industrial Databases
Applied Intelligence
An Implementation of Logical Analysis of Data
IEEE Transactions on Knowledge and Data Engineering
Boolean Analysis of Incomplete Examples
SWAT '96 Proceedings of the 5th Scandinavian Workshop on Algorithm Theory
A Comparison of Several Approaches to Missing Attribute Values in Data Mining
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
Discovering Knowledge in Data: An Introduction to Data Mining
Discovering Knowledge in Data: An Introduction to Data Mining
A Quantitative Study of the Effect of Missing Data in Classifiers
CIT '05 Proceedings of the The Fifth International Conference on Computer and Information Technology
Comprehensive vs. comprehensible classifiers in logical analysis of data
Discrete Applied Mathematics
Missing value imputation based on data clustering
Transactions on computational science I
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This paper investigates the application of a data mining technique called Logical Analysis of Data (LAD) to condition-based maintenance. The existing classification techniques are mainly based on statistical analysis and modeling approaches. This paper presents a classification technique based on combinatory and Boolean theory. It is shown that LAD is particularly suitable for detecting the state of equipment because of its new way of pre-processing noisy and missing data. A numerical example and an application are presented.