Data preparation for data mining
Data preparation for data mining
Detecting Group Differences: Mining Contrast Sets
Data Mining and Knowledge Discovery
Soft Computing and Fuzzy Logic
IEEE Software
An Algorithm for Multi-relational Discovery of Subgroups
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
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
Rule Evaluation Measures: A Unifying View
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Mining border descriptions of emerging patterns from dataset pairs
Knowledge and Information Systems
Impact of imputation of missing values on classification error for discrete data
Pattern Recognition
KEEL: a software tool to assess evolutionary algorithms for data mining problems
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Evolutionary and Metaheuristics based Data Mining (EMBDM); Guest Editors: José A. Gámez, María J. del Jesús, José M. Puerta
Expert Systems with Applications: An International Journal
POP algorithm: Kernel-based imputation to treat missing values in knowledge discovery from databases
Expert Systems with Applications: An International Journal
Missing Value Imputation Using a Semi-supervised Rank Aggregation Approach
SBIA '08 Proceedings of the 19th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
Discovering patterns of missing data in survey databases: An application of rough sets
Expert Systems with Applications: An International Journal
Estimating confidence intervals for structural differences between contrast groups with missing data
Expert Systems with Applications: An International Journal
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
The Journal of Machine Learning Research
Fuzzy methods in machine learning and data mining: Status and prospects
Fuzzy Sets and Systems
Mining incomplete survey data through classification
Knowledge and Information Systems
Diagnose the mild cognitive impairment by constructing Bayesian network with missing data
Expert Systems with Applications: An International Journal
IEEE Transactions on Fuzzy Systems
Missing data analysis with fuzzy C-Means: A study of its application in a psychological scenario
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
SD-map: a fast algorithm for exhaustive subgroup discovery
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Handling missing attribute values in preterm birth data sets
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Evolutionary fuzzy rule extraction for subgroup discovery in a psychiatric emergency department
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Evolutionary Fuzzy Systems
An overview on subgroup discovery: foundations and applications
Knowledge and Information Systems
Multiobjective evolutionary induction of subgroup discovery fuzzy rules: a case study in marketing
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
Missing data imputation for fuzzy rule-based classification systems
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Knowledge Extraction from Low Quality Data: Theoretical, Methodological and Practical Issues
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
A Novel Framework for Imputation of Missing Values in Databases
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Evolutionary Fuzzy Rule Induction Process for Subgroup Discovery: A Case Study in Marketing
IEEE Transactions on Fuzzy Systems
Hi-index | 12.05 |
Subgroup discovery is a descriptive data mining technique which aims at obtaining interesting rules through supervised learning. In general, there are no works analysing the consequences of the presence of missing values in data in this task, although improper handling of this type of data in the analysis may introduce bias and can result in misleading conclusions being drawn from a research study. This paper presents a study on the effect of using the most relevant approaches for pre-processing of missing values in a determined group of algorithms, the evolutionary fuzzy systems for subgroup discovery. The experimental study presented in this paper show that, among the methods studied, the KNNI pre-processing approach for missing values obtains the best results in evolutionary fuzzy systems for subgroup discovery.