The Strength of Weak Learnability
Machine Learning
Using statistical testing in the evaluation of retrieval experiments
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Floating search methods in feature selection
Pattern Recognition Letters
Boosting a weak learning algorithm by majority
Information and Computation
Machine Learning
Feature Selection: Evaluation, Application, and Small Sample Performance
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
The Random Subspace Method for Constructing Decision Forests
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the First International Workshop on Multiple Classifier Systems
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Disconnected Handwritten Numeral Image Recognition
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Creation of Classifier Ensembles for Handwritten Word Recognition Using Feature Selection Algorithms
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
EROS: Ensemble rough subspaces
Pattern Recognition
Genetic algorithm-based feature set partitioning for classification problems
Pattern Recognition
Genetic algorithm-based feature set partitioning for classification problems
Pattern Recognition
Efficient Online Classification Using an Ensemble of Bayesian Linear Logistic Regressors
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Computational Statistics & Data Analysis
Binary segmentation with neural validation for cursive handwriting recognition
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Selecting features from multiple feature sets for SVM committee-based screening of human larynx
Expert Systems with Applications: An International Journal
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
Binary segmentation algorithm for English cursive handwriting recognition
Pattern Recognition
Constructing rough decision forests
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Observations on boosting feature selection
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Off-line cursive script recognition: current advances, comparisons and remaining problems
Artificial Intelligence Review
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The study of multiple classifier systems has become an area of intensive research in pattern recognition recently. Also in handwriting recognition, systems combining several classifiers have been investigated. In this paper new methods for the creation of classifier ensembles based on feature selection algorithms are introduced. Those new methods are evaluated and compared to existing approaches in the context of handwritten word recognition, using a hidden Markov model recognizer as basic classifier.