Machine Learning tools are increasingly being applied to analyze data from microarray experiments. These include ensemble methods where weighted votes of constructed base classifiers are used to classify data. We compare the performance of AdaBoost, bagging and BagBoost on gene expression data from the yeast cell cycle. AdaBoost was found to be more effective for the data than bagging. BagBoost...

The problem of large-scale simultaneous hypothesis testing is revisited. Bagging and subagging procedures are put forth with the purpose of improving the discovery power of the tests. The procedures are implemented in both simulated and real data. It is shown that bagging and subagging significantly improve power at the cost of a small increase in false discovery rate with the proposed ‘maximum...

In this paper, a dual perturb and combine algorithm is proposed which consists in producing the perturbed predictions at the prediction stage using only one model. To this end, the attribute vector of a test case is perturbed several times by an additive random noise, the model is applied to each of these perturbed vectors and the resulting predictions are aggregated. An analytical version of t...

Discriminative probabilistic models are very popular in NLP because of the latitude they afford in designing features. But training involves complex trade-offs among weights, which can be dangerous: a few highlyindicative features can swamp the contribution of many individually weaker features, causing their weights to be undertrained. Such a model is less robust, for the highly-indicative feat...

Discriminatively-trained probabilistic models are very popular in NLP because of the latitude they afford in designing features. But training involves complex trade-offs among weights, which can be dangerous: a few highlyindicative features can swamp the contribution of many individually weaker features, causing their weights to be undertrained. Such a model is less robust, for the highly-indic...

The Heidelberg Retina Tomograph (HRT) provides topographic images of the optic nerve head by scanning the eye with a 670nm laser. As a precondition to medical analysis, the optic nerve head has to be outlined manually in clinical practise. Swindale et al. (2000) suggest automated classification of HRT images by a non-linear approximation of the image using the fitted parameters of a non-linear ...

There has been an increasing interest in applying machine learning methods in urban energy assessment. This research implemented six statistical learning methods in estimating domestic gas and electricity using both physical and socio-economic explanatory variables in London. The input variables include dwelling types, household tenure, household composition, council tax band, population age gr...

In order to obtain morphological information of unlabeled galaxies, we present an unsupervised machine-learning (UML) method for classification which can be summarized as two aspects: (1) the methodology convolutional autoencoder (CAE) is used reduce dimensions and extract features from imaging data; (2) bagging-based multiclustering model proposed classifications with high confidence at cost r...

In bagging Bre94a] one uses bootstrap replicates of the training set Efr79, ET93] to improve a learning algorithm's performance, often by tens of percent. This paper presents several ways that stacking Wol92b, Bre92] can be used in concert with the bootstrap procedure to achieve a further improvement on the performance of bagging for some regression problems. In particular, in some of the work ...