An introduction to boosting and leveraging
Advanced lectures on machine learning
Robust and Accurate Cancer Classification with Gene Expression Profiling
CSB '05 Proceedings of the 2005 IEEE Computational Systems Bioinformatics Conference
A maximally diversified multiple decision tree algorithm for microarray data classification
WISB '06 Proceedings of the 2006 workshop on Intelligent systems for bioinformatics - Volume 73
A new classification model with simple decision rule for discovering optimal feature gene pairs
Computers in Biology and Medicine
Cancer classification using Rotation Forest
Computers in Biology and Medicine
Cancer classification from serial analysis of gene expression with event models
Applied Intelligence
Evidence Contrary to the Statistical View of Boosting
The Journal of Machine Learning Research
Computational Biology and Chemistry
Patient-centered yes/no prognosis using learning machines
International Journal of Data Mining and Bioinformatics
Computational Statistics & Data Analysis
Gene boosting for cancer classification based on gene expression profiles
Pattern Recognition
When is 'nearest neighbour' meaningful: A converse theorem and implications
Journal of Complexity
International Journal of Bioinformatics Research and Applications
Inference from Low Precision Transcriptome Data Representation
Journal of Signal Processing Systems
Computers in Biology and Medicine
Expert Systems with Applications: An International Journal
Cancer identification based on DNA microarray data
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
Bagging multiple comparisons from microarray data
ISBRA'08 Proceedings of the 4th international conference on Bioinformatics research and applications
Expectation Propagation for microarray data classification
Pattern Recognition Letters
Decision forest for classification of gene expression data
Computers in Biology and Medicine
Wavelet selection for disease classification by DNA microarray data
Expert Systems with Applications: An International Journal
On the distance concentration awareness of certain data reduction techniques
Pattern Recognition
A low variance error boosting algorithm
Applied Intelligence
Artificial Intelligence in Medicine
Uncorrelated trace ratio linear discriminant analysis for undersampled problems
Pattern Recognition Letters
Boosting based conditional quantile estimation for regression and binary classification
MICAI'10 Proceedings of the 9th Mexican international conference on Artificial intelligence conference on Advances in soft computing: Part II
Multiclass Kernel-Imbedded Gaussian Processes for Microarray Data Analysis
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
An experimental comparison of gene selection by Lasso and Dantzig selector for cancer classification
Computers in Biology and Medicine
Robust classification ensemble method for microarray data
International Journal of Data Mining and Bioinformatics
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Combined gene selection methods for microarray data analysis
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Image similarity and asymmetry to improve computer-aided detection of breast cancer
IWDM'06 Proceedings of the 8th international conference on Digital Mammography
Robust ensemble learning for cancer diagnosis based on microarray data classification
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Increasing classification accuracy by combining adaptive sampling and convex pseudo-data
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Expert Systems with Applications: An International Journal
Regularized orthogonal linear discriminant analysis
Pattern Recognition
Combining gene expression and interaction network data to improve kidney lesion score prediction
International Journal of Bioinformatics Research and Applications
Event models for tumor classification with SAGE gene expression data
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part II
Functional gradient ascent for Probit regression
Pattern Recognition
Sparse sufficient dimension reduction using optimal scoring
Computational Statistics & Data Analysis
Stabilizing the lasso against cross-validation variability
Computational Statistics & Data Analysis
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Motivation: Microarray experiments are expected to contribute significantly to the progress in cancer treatment by enabling a precise and early diagnosis. They create a need for class prediction tools, which can deal with a large number of highly correlated input variables, perform feature selection and provide class probability estimates that serve as a quantification of the predictive uncertainty. A very promising solution is to combine the two ensemble schemes bagging and boosting to a novel algorithm called BagBoosting. Results: When bagging is used as a module in boosting, the resulting classifier consistently improves the predictive performance and the probability estimates of both bagging and boosting on real and simulated gene expression data. This quasi-guaranteed improvement can be obtained by simply making a bigger computing effort. The advantageous predictive potential is also confirmed by comparing BagBoosting to several established class prediction tools for microarray data. Availability: Software for the modified boosting algorithms, for benchmark studies and for the simulation of microarray data are available as an R package under GNU public license at http://stat.ethz.ch/~dettling/bagboost.html