
Apache Spark
 Referenced in 61 articles
[sw28418]
 general cluster computing system for Big Data. It provides highlevel APIs in Scala, Java...

KNIME
 Referenced in 24 articles
[sw06790]
 entire analysis process: data access, data transformation, initial investigation, powerful predictive analytics, visualisation and reporting ... well as worldclass support. Robust big data extensions are available for distributed frameworks such...

bmrm
 Referenced in 23 articles
[sw11016]
 learning which make it powerful for big data analysis. The applications includes: structured prediction, linear...

Finito
 Referenced in 18 articles
[sw38276]
 Faster, Permutable Incremental Gradient Method for Big Data Problems. Recent advances in optimization theory have...

GHadoop
 Referenced in 12 articles
[sw08480]
 security framework in GHadoop for big data computing across distributed cloud data centres. MapReduce...

BigDatalog
 Referenced in 5 articles
[sw27496]
 BigDatalog is a Datalog system for Big Data Analytics first presented at SIGMOD ... paper Big Data Analytics with Datalog Queries on Spark for details. BigDatalog is implemented...

jLab
 Referenced in 7 articles
[sw25248]
 Matlab, with ∼300 routines for big data analysis, signal processing, mapping, and oceanographic applications. Version...

biglasso
 Referenced in 5 articles
[sw19509]
 biglasso. Extending Lasso Model Fitting to Big Data. Extend lasso and elasticnet model fitting ... ultrahighdimensional, multigigabyte data sets that cannot be loaded into memory. It’s much ... ncvreg’, thus allowing for very powerful big data analysis even with an ordinary laptop...

SOFAR
 Referenced in 7 articles
[sw31665]
 scale association network learning. Many modern big data applications feature large scale in both numbers...

h2o
 Referenced in 7 articles
[sw17104]
 open source math engine for big data that computes parallel distributed machine learning algorithms such...

ROSEFWRF
 Referenced in 3 articles
[sw23974]
 winner algorithm for the ECBDL’14 big data competition: An extremely imbalanced big data bioinformatics ... obtain and store large quantities of data about cells, proteins, genes, etc., that should ... under these circumstances, known as imbalanced big data classification, may not be straightforward for most ... methodology that won the ECBDL’14 big data challenge for a bioinformatics big data problem...

HBase
 Referenced in 6 articles
[sw10948]
 random, realtime read/write access to your Big Data. This project’s goal is the hosting...

DSCOVR
 Referenced in 6 articles
[sw28397]
 asynchronous distributed optimization. Machine learning with big data often involves large optimization models. For distributed...

HRMS
 Referenced in 3 articles
[sw29384]
 useful toolkit for model averaging in big data analytics. Frequentist model averaging has been demonstrated ... deal with model uncertainty in big data analysis. In contrast with a conventional data ... number of regressors in a big data set is usually quite large, which leads ... simulation results and empirical exercise with big data analytics demonstrate the superiority of our HRMS...

QuickhullDisk
 Referenced in 5 articles
[sw31399]
 Golin in 1995, particularly for big data. QuickhullDisk is approximately 2.6 times faster than...

AMIDST
 Referenced in 5 articles
[sw21741]
 distributed computing clusters managed by modern big data processing tools like Apache Spark or Apache...

PyDMD
 Referenced in 4 articles
[sw38466]
 order to deal with noisy data, big dataset, or spurious data for example. In PyDMD...

FlinkCL
 Referenced in 2 articles
[sw27868]
 heterogeneous CPUGPU clusters for big data. Research on inmemory big data management ... memory capacity and the explosion in big data. By offering an efficient inmemory distributed ... proven to be outstanding for processing big data. This paper proposes FlinkCL, an inmemory...

pbdR
 Referenced in 4 articles
[sw14584]
 Programming with Big Data in R” project (pbdR) is a set of R packages...

Vertica
 Referenced in 2 articles
[sw27059]
 very first line of code for Big Data analytics. It is designed ... data warehouses and other big data workloads where speed, scalability, simplicity, and openness are crucial ... anywhere delivers on the promise of big data analytics like no other solution...