8 Result(s)
within
Berthold Lausen
Probability and Statistics in Computer Science
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Chapter and Conference Paper
Ensemble of Subset of k-Nearest Neighbours Models for Class Membership Probability Estimation
Combining multiple classifiers can give substantial improvement in prediction performance of learning algorithms especially in the presence of non-informative features in the data sets. This technique can ...
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Chapter and Conference Paper
Analysis of ChIP-seq Data Via Bayesian Finite Mixture Models with a Non-parametric Component
In large discrete data sets which requires classification into signal and noise components, the distribution of the signal is often very bumpy and does not follow a standard distribution. Therefore the signa...
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Chapter and Conference Paper
Minimizing Redundancy Among Genes Selected Based on the Overlap** Analysis
For many functional genomic experiments, identifying the most characterizing genes is a main challenge. Both the prediction accuracy and interpretability of a classifier could be enhanced by performing the cla...
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Chapter and Conference Paper
An Ensemble of Optimal Trees for Class Membership Probability Estimation
Machine learning methods can be used for estimating the class membership probability of an observation. We propose an ensemble of optimal trees in terms of their predictive performance. This ensemble is formed...
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Article
Classification of repeated measurements data using tree-based ensemble methods
In many medical applications, longitudinal data sets are available. Longitudinal data, as well as observations from paired organs, show a dependency structure which should be respected in the evaluation. Adler...
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Chapter and Conference Paper
Glaucoma Diagnosis by Indirect Classifiers
Medical decision making is based on various diagnostic measurements and the evaluation of anamnestic information. For example glaucoma diagnosis is based on several direct and indirect assessments of the eye. ...
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Chapter and Conference Paper
Bioinformatics and Classification: The Analysis of Genome Expression Data
The availability of microarray data caused a new interest in clustering and classification methods. DNA microarrays are likely to play an important role for diagnosis and prognosis in clinical practice. Using ...
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Chapter and Conference Paper
Bagging Combined Classifiers
Aggregated classifiers have proven to be successful in reducing misclassification error in a wide range of classification problems. One of the most popular is bagging. But often simple procedures perform comp...
