Statistical analysis with missing data
Statistical analysis with missing data
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
Reduction Techniques for Instance-BasedLearning Algorithms
Machine Learning
Machine Learning
Advances in Instance Selection for Instance-Based Learning Algorithms
Data Mining and Knowledge Discovery
Nearest Neighbor Search: A Database Perspective
Nearest Neighbor Search: A Database Perspective
Stratification for scaling up evolutionary prototype selection
Pattern Recognition Letters
A memetic algorithm for evolutionary prototype selection: A scaling up approach
Pattern Recognition
Making CN2-SD subgroup discovery algorithm scalable to large size data sets using instance selection
Expert Systems with Applications: An International Journal
Discovering patterns of missing data in survey databases: An application of rough sets
Expert Systems with Applications: An International Journal
The Top Ten Algorithms in Data Mining
The Top Ten Algorithms in Data Mining
Toward breast cancer survivability prediction models through improving training space
Expert Systems with Applications: An International Journal
Performance evaluation for classification methods: A comparative simulation study
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Framework for eliciting knowledge for a medical laboratory diagnostic expert system
Expert Systems with Applications: An International Journal
Instance Selection and Construction for Data Mining
Instance Selection and Construction for Data Mining
Using evolutionary algorithms as instance selection for data reduction in KDD: an experimental study
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
Analysis of data complexity measures for classification
Expert Systems with Applications: An International Journal
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There is a frequent situation in data mining where data collected must be used in real time to support decisions and they could present missing or non consistent values. The objective of this proposal consists of the recovery of missing values and verifies the consistency and integrity of the provided, in order to increase the information to support decisions. To address this, a predictive-collaborative model has been designed. It is composed of different predictive models generated by means of a training set and classifier selection algorithm. The combined suggestions of these predictive models are offered to support decisions. As case of study, the psychiatric emergency department at the Doce de Octubre Hospital in Madrid has been considered, where the response time is critical and the data are acquired in a stress situation which affects the quality of data significantly.