- Referenced in 1060 articles
- BayesDA: Functions and Datasets for the book ”Bayesian Data Analysis” Functions for Bayesian Data Analysis ... with datasets from the book ”Bayesian data Analysis (second edition)” by Gelman, Carlin, Stern ... Rubin. Not all datasets yet, hopefully completed soon...
- Referenced in 598 articles
- Memory Processes (Jan Beran) – Data and Functions. Datasets and Functionality from the textbook Jan Beran...
- Referenced in 281 articles
- package MASS: Support Functions and Datasets for Venables and Ripley’s MASS , Functions and datasets...
- Referenced in 248 articles
- calculation over extremely large datasets. The arrival of MapReduce provides a chance to utilize commodity...
- Referenced in 154 articles
- ParaView was developed to analyze extremely large datasets using distributed memory computing resources ... supercomputers to analyze datasets of terascale as well as on laptops for smaller data...
- Referenced in 125 articles
- construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification...
- Referenced in 170 articles
- Berkeley Segmentation Dataset and Benchmark. A database of human segmented natural images and its application...
- Referenced in 99 articles
- datamining and knowledge acquisition from large datasets. The paper presents results of experiments using several ... artificial and real-world datasets. The results demonstrate that DistAl compares favorably with other learning...
- Referenced in 66 articles
- subsets of the 80 million tiny images dataset. They were collected by Alex Krizhevsky, Vinod ... Nair, and Geoffrey Hinton. The CIFAR-10 dataset consists of 60000 32x32 colour images ... training images and 10000 test images. The dataset is divided into five training batches ... images from each class. The CIFAR-100 dataset: This dataset is just like the CIFAR...
- Referenced in 108 articles
- frequent graph-based pattern mining in graph datasets and propose a novel algorithm called gSpan...
- Referenced in 52 articles
- little as 1% of a large dataset for its explicit evaluation. To generate this nonlinear ... surface, the entire dataset is used as a constraint in an optimization problem with very ... small randomly selected portion of the dataset, is better than that of a conventional support ... surface that explicitly depends on the entire dataset, and much better than a conventional...
- Referenced in 93 articles
- especially suited for learning from large datasets. Our approach also extends to non-linear kernels...
- Referenced in 92 articles
- ImageNet is an image dataset organized according to the WordNet hierarchy. Each meaningful concept...
- Referenced in 90 articles
- spatial/spatio-temporal modelling and prediction with large datasets. The approach, discussed in Cressie and Johannesson...
- Referenced in 52 articles
- allows you to ask sophisticated queries against datasets derived from Wikipedia and to link other ... datasets on the Web to Wikipedia data. We describe the extraction of the DBpedia datasets ... status of interlinking DBpedia with other open datasets on the Web and outline how DBpedia...
- Referenced in 63 articles
- ROBPCA yields more accurate estimates at noncontaminated datasets and more robust estimates at contaminated data ... outliers. We apply the algorithm to several datasets from chemometrics and engineering...
- Referenced in 82 articles
- enjoys many desirable properties. Using real-world datasets, we demonstrate that LOF can be used...
- Referenced in 46 articles
- compares two protein datasets and reports similar matches between them; cd-hit-est clusters ... compares two nucleotide datasets. All these programs can handle huge datasets with millions of sequences...
- Referenced in 45 articles
- BioGRID: A general repository for interaction datasets. Access to unified datasets of protein and genetic ... interaction data. Full or user-defined datasets are freely downloadable as tab-delimited text files...