C4.5: programs for machine learning
C4.5: programs for machine learning
Decision Combination in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
Machine Learning
Machine Learning - Special issue on learning with probabilistic representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
On combining classifiers using sum and product rules
Pattern Recognition Letters
The use of bigrams to enhance text categorization
Information Processing and Management: an International Journal
How to Make Stacking Better and Faster While Also Taking Care of an Unknown Weakness
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Methods for Designing Multiple Classifier Systems
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Combination of Face Classifiers for Person Identification
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
Using diversity measures for generating error-correcting output codes in classifier ensembles
Pattern Recognition Letters
Rotation Forest: A New Classifier Ensemble Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Using diversity of errors for selecting members of a committee classifier
Pattern Recognition
Modeling intrusion detection system using hybrid intelligent systems
Journal of Network and Computer Applications - Special issue: Network and information security: A computational intelligence approach
Calligraphic Interfaces: Classifier combination for sketch-based 3D part retrieval
Computers and Graphics
On diversity and accuracy of homogeneous and heterogeneous ensembles
International Journal of Hybrid Intelligent Systems
An experimental comparison of performance measures for classification
Pattern Recognition Letters
Advanced Engineering Informatics
McPAD: A multiple classifier system for accurate payload-based anomaly detection
Computer Networks: The International Journal of Computer and Telecommunications Networking
A systematic analysis of performance measures for classification tasks
Information Processing and Management: an International Journal
Semi-random subspace method for face recognition
Image and Vision Computing
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
On learning algorithm selection for classification
Applied Soft Computing
Performance evaluation for classification methods: A comparative simulation study
Expert Systems with Applications: An International Journal
Integration of heterogeneous models to predict consumer behavior
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Modern Applied Statistics with S
Modern Applied Statistics with S
Estimating continuous distributions in Bayesian classifiers
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
A bias-variance-complexity trade-off framework for complex system modeling
ICCSA'06 Proceedings of the 6th international conference on Computational Science and Its Applications - Volume Part I
Semi-supervised ensemble classification in subspaces
Applied Soft Computing
Illumination-Invariant color image correction
IWICPAS'06 Proceedings of the 2006 Advances in Machine Vision, Image Processing, and Pattern Analysis international conference on Intelligent Computing in Pattern Analysis/Synthesis
A study of the robustness of KNN classifiers trained using soft labels
ANNPR'06 Proceedings of the Second international conference on Artificial Neural Networks in Pattern Recognition
Financial distress prediction using support vector machines: Ensemble vs. individual
Applied Soft Computing
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The automatic detection of construction materials in images acquired on a construction site has been regarded as a critical topic. Recently, several data mining techniques have been used as a way to solve the problem of detecting construction materials. These studies have applied single classifiers to detect construction materials-and distinguish them from the background-by using color as a feature. Recent studies suggest that combining multiple classifiers (into what is called a heterogeneous ensemble classifier) would show better performance than using a single classifier. However, the performance of ensemble classifiers in construction material detection is not fully understood. In this study, we investigated the performance of six single classifiers and potential ensemble classifiers on three data sets: one each for concrete, steel, and wood. A heterogeneous voting-based ensemble classifier was created by selecting base classifiers which are diverse and accurate; their prediction probabilities for each target class were averaged to yield a final decision for that class. In comparison with the single classifiers, the ensemble classifiers performed better in the three data sets overall. This suggests that it is better to use an ensemble classifier to enhance the detection of construction materials in images acquired on a construction site.