Search Results - "Frank, Eibe"

Regularisation of neural networks by enforcing Lipschitz continuity by Gouk, Henry, Frank, Eibe, Pfahringer, Bernhard, Cree, Michael J.

“…We investigate the effect of explicitly enforcing the Lipschitz continuity of neural networks with respect to their inputs. To this end, we provide a simple…”
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Classifier chains for multi-label classification by Read, Jesse, Pfahringer, Bernhard, Holmes, Geoff, Frank, Eibe

“…The widely known binary relevance method for multi-label classification, which considers each label as an independent binary problem, has often been overlooked…”
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Accelerating the XGBoost algorithm using GPU computing by Mitchell, Rory, Frank, Eibe

“…We present a CUDA-based implementation of a decision tree construction algorithm within the gradient boosting library XGBoost. The tree construction algorithm…”
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Improving Naive Bayes for Regression with Optimized Artificial Surrogate Data by Mayo, Michael, Frank, Eibe

“…Can we evolve better training data for machine learning algorithms? To investigate this question we use population-based optimization algorithms to generate…”
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GPUTreeShap: massively parallel exact calculation of SHAP scores for tree ensembles by Mitchell, Rory, Frank, Eibe, Holmes, Geoffrey

“…SHapley Additive exPlanation (SHAP) values (Lundberg & Lee, 2017) provide a game theoretic interpretation of the predictions of machine learning models based…”
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Data mining in bioinformatics using Weka by Frank, Eibe, Hall, Mark, Trigg, Len, Holmes, Geoffrey, Witten, Ian H.

“…The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection—common…”
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DNA methylation-associated colonic mucosal immune and defense responses in treatment-naïve pediatric ulcerative colitis by Harris, R Alan, Nagy-Szakal, Dorottya, Mir, Sabina AV, Frank, Eibe, Szigeti, Reka, Kaplan, Jess L, Bronsky, Jiri, Opekun, Antone, Ferry, George D, Winter, Harland, Kellermayer, Richard

“…Inflammatory bowel diseases (IBD) are emerging globally, indicating that environmental factors may be important in their pathogenesis. Colonic mucosal…”
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Gene selection from microarray data for cancer classification—a machine learning approach by Wang, Yu, Tetko, Igor V., Hall, Mark A., Frank, Eibe, Facius, Axel, Mayer, Klaus F.X., Mewes, Hans W.

“…A DNA microarray can track the expression levels of thousands of genes simultaneously. Previous research has demonstrated that this technology can be useful in…”
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Interactive machine learning: letting users build classifiers by WARE, MALCOLM, FRANK, EIBE, HOLMES, GEOFFREY, HALL, MARK, WITTEN, IAN H

“…According to standard procedure, building a classifier using machine learning is a fully automated process that follows the preparation of training data by a…”
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WekaPyScript: Classification, Regression, and Filter Schemes for WEKA Implemented in Python by Beckham, Christopher, Hall, Mark, Frank, Eibe

“…WekaPyScript is a package for the machine learning software WEKA that allows learning algorithms and preprocessing methods for classification and regression to…”
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Determining Word-Emotion Associations from Tweets by Multi-label Classification by Bravo-Marquez, Felipe, Frank, Eibe, Mohammad, Saif M., Pfahringer, Bernhard

“…The automatic detection of emotions in Twitter posts is a challenging task due to the informal nature of the language used in this platform. In this paper, we…”
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Learning a concept-based document similarity measure by Huang, Lan, Milne, David, Frank, Eibe, Witten, Ian H.

“…Document similarity measures are crucial components of many text‐analysis tasks, including information retrieval, document classification, and document…”
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Introducing Machine Learning Concepts with WEKA by Smith, Tony C, Frank, Eibe

“…This chapter presents an introduction to data mining with machine learning. It gives an overview of various types of machine learning, along with some…”
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Classifier Chains: A Review and Perspectives by Read, Jesse, Pfahringer, Bernhard, Holmes, Geoffrey, Frank, Eibe

“…The family of methods collectively known as classifier chains has become a popular approach to multi-label learning problems. This approach involves chaining…”
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Large scale K-means clustering using GPUs by Li, Mi, Frank, Eibe, Pfahringer, Bernhard

“…The k -means algorithm is widely used for clustering, compressing, and summarizing vector data. We present a fast and memory-efficient GPU-based algorithm for…”
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Building a Twitter opinion lexicon from automatically-annotated tweets by Bravo-Marquez, Felipe, Frank, Eibe, Pfahringer, Bernhard

“…•We propose a supervised model for expanding an opinion lexicon for Twitter.•We combine automatically annotated tweets with existing hand-made opinion…”
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WekaDeeplearning4j: A deep learning package for Weka based on Deeplearning4j by Lang, Steven, Bravo-Marquez, Felipe, Beckham, Christopher, Hall, Mark, Frank, Eibe

“…Deep learning is a branch of machine learning that generates multi-layered representations of data, commonly using artificial neural networks, and has improved…”
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Feature extractor stacking for cross-domain few-shot learning by Wang, Hongyu, Frank, Eibe, Pfahringer, Bernhard, Mayo, Michael, Holmes, Geoffrey

“…Cross-domain few-shot learning (CDFSL) addresses learning problems where knowledge needs to be transferred from one or more source domains into an…”
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Augmenting NIR Spectra in deep regression to improve calibration by Wohlers, Mark, McGlone, Andrew, Frank, Eibe, Holmes, Geoffrey

“…Deep learning, particularly with convolutional neural networks, shows promise in modelling near-infrared spectroscopy (NIRS), but the lack of robust…”
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Accurate photometric redshift probability density estimation – method comparison and application by Rau, Markus Michael, Seitz, Stella, Brimioulle, Fabrice, Frank, Eibe, Friedrich, Oliver, Gruen, Daniel, Hoyle, Ben

“…We introduce an ordinal classification algorithm for photometric redshift estimation, which significantly improves the reconstruction of photometric redshift…”
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