Search Results for "big data visualization" - Page 4
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Showing 110 open source projects for "big data visualization"
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Red-RF
Reduced Random Forest for big data
Red(uced)-RF, a new type of Random Forests that adopts dynamic data reduction and weighted upvoting techniques. Red-RF is favorably applicable to big data: it demonstrates an accurate and efficient performance while achieving a considerable data reduction w.r.t. dataset size. Manuscripts available on IEEE Xplore: H. Mohsen, H. Kurban, K. Zimmer, M. Jenne and M. Dalkilic. Red-RF: Reduced Random Forests using priority voting & dynamic data reduction. ... -
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ankus
Data Mining and Machine Learning Algorithms based on MapReduce
[The feature of ankus] * ankus is a 'web-based big data mining project and tool'. - MapReduce-based data mining/machine learning algorithms library - Hadoop-based distributed bigdata system - offering a web-based GUI for easy use [The ankus project & License] * The ankus project consists of three as an open source. * ankus has Dual licensed under the community and commercial licenses -
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GOBIG is a toolbox that can be used for detecting genetic variations. The project is intended to handle big data. What's more important is that it be used to detect clusters of SNP variants. It is the intention to use the toolbox with common and rare variants. To use it, for example, to find the genetic map of genes causing complex diseases.
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Universal Java Matrix Package
sparse and dense matrix, linear algebra, visualization, big data
The Universal Java Matrix Package (UJMP) is an open source Java library which provides sparse and dense matrix classes, as well as a large number of calculations for linear algebra such as matrix multiplication or matrix inverse. Operations such as mean, correlation, standard deviation, replacement of missing values or the calculation of mutual information are supported, too. The Universal Java Matrix Package provides various visualization methods, import and export filters for a large... -
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BEAR
CBR Meets Big Data
Case-based regression learner for big data. The package contains source and binary files for running BEAR's method. BEAR utilizes EAR4 and locality sensitive hashing in its implementation. -
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PROPER is a package for visual evaluation of ranking classifiers for biological big data mining studies in the mathematical language MATLAB. It is an efficient tool for optimization and comparison of the state-of-the-art ranking classifiers by generating over 20 different high quality two- and three-dimensional performance curves.
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Relation Tags
Source code for be able to use Relation Tags.
...Please read "readme" file. It is recommended to use a binary matrix class like BinMatrix in order to have enough speed for calculations of implicit relations in a system of bogus tags with big data. Need to be compiled with C++11 and Qt libraries -
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Sample Level Musical Timeline
Sample Level Modulation of Musical Timeline
Sample Level Modulation of Musical Timeline Mingfeng Zhang Dept. of Electrical and Computer Engineering, University of Rochester In this toolbox we provide signal processing tools to allocate music events (samples of musical notes) to specified time locations with sample level accuracy. In this implementation, we use computational tools to add in micro-timing variations in J.S. Bach four-part chorales as a "visualizer" for big data. By extracting data patterns from multiple time scales, we implement a tool that musicians can perform the big data at different resolutions. This toolbox will need the following supporting toolboxes: MIDI TOOLBOX https://www.jyu.fi/hum/laitokset/musiikki/en/research/coe/materials/miditoolbox MIR TOOLBOX https://www.jyu.fi/hum/laitokset/musiikki/en/research/coe/materials/mirtoolbox Please add the path in MATLAB for these two toolbox. ... -
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PROPER is a package for visual evaluation of ranking classifiers for biological big data mining studies in the mathematical language MATLAB. It is an efficient tool for optimization and comparison of the state-of-the-art ranking classifiers by generating over 20 different high quality two- and three-dimensional performance curves.
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Chinese I Ching R Algorithms
Chinese I Ching Algorithms implemented with R programming
...This project tries to realize these algorithms with statistical programming. Overcoming the long span has important meanings. First, we can verify the validity of algorithm with big data. Second, we can put them into unprecedented wide application in the age of data. Third, the unique inspection of I Ching that linked "all the universe" open new eyes for us in thought and methodology about interdisciplinary use of data. This program is open-source for human. If you are interested in it, welcome to discuss and work together. -
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Chordalysis
Log-linear analysis (data modelling) for high-dimensional data
...However, due to its exponential nature, previous approaches did not allow scale-up to more than a dozen variables. We present here Chordalysis, a log-linear analysis method for big data. Chordalysis exploits recent discoveries in graph theory by representing complex models as compositions of triangular structures, also known as chordal graphs. Chordalysis makes it possible to discover the structure of datasets with thousands of variables on a standard desktop computer. Associated papers at ICDM 2013, ICDM 2014 and SDM 2015 can be found at http://www.francois-petitjean.com/Research/ YourKit is supporting Chordalysis open source project with its full-featured Java Profiler. ... -
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BIRT Report Designer
Open Source Reporting & Data Visualization Platform
...With a flexible Open Data Access framework, developers can write custom data drivers to access data from any source, including Big Data sources like Apache Hadoop, Cassandra, and MongoDB, along with all traditional relational databases, Flat Files, XML data streams, and data stored in proprietary systems. Built for embedding, BIRT includes APIs for data access, chart generation, output formats, content execution, and integration within larger applications. -
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BIRT iHub F-Type
Free report server for creating data-driven apps
...With out-of-the-box Big Data support, BIRT iHub F-Type connects to all relational databases and allows unlimited data-in for creating data visualizations and dynamic report views. -
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giServer
giServer the easy to use and extensible batch and integration server
...Instead of using complex XML configuration files an elaborate GUI for batch job management is included. Some possible usage scenarios are: - Automatic processing of incoming data files - Big Data applications - Process automation - Data Mining/Aggregation applications - Automatic Reporting - Processing and analysis of database records -
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FrincBackup
Incremtal backup tool supporting removable storage devices
FrincBackup means free incremental backup. It is developed for backing up a x TB NAS with storage devices in a logical volume to multiple removable storage devices, such as 500 GB USB hard drives. Files are backuped as files (not as an archive) and are readable without the need of a tool and without the need of FrincBackup itself (allthough there is a restore mode for better handling). -
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Flamingo Project
Workflow Designer, Hive Editor, Pig Editor, File System Browser
Flamingo is a open-source Big Data Platform that combine a Ajax Rich Web Interface + Workflow Engine + Workflow Designer + MapReduce + Hive Editor + Pig Editor. 1. Easy Tool for big data 2. Use comfortable in Hadoop EcoSystem projects 3. Based GPL V3 License Supporting Pig IDE, Hive IDE, HDFS Browser, Scheduler, Hadoop Job Monitoring, Workflow Engine, Workflow Designer, MapReduce. -
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Streams for IBM i
Batch performance boosting and Big Data framework for IBM i
Streamd for IBM i is a suite of tools for IBM i (previously known as AS/400 and iSeries) that can significantly improve performance characteristics of batch processes. Due to extensive use of parallel programming techniques Streams for IBM i delivers significant performance improvements for single streamed batch jobs. Streams for IBM i can split an existing batch process into a number of concurrent streams, completely eliminate backup-related delays, introduce new robust recovery policies... -
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iOVFDT
iOVFDT algorithm of incremental decision tree
How to extract meaningful information from big data has been a popular open problem. Decision tree, which has a high degree of knowledge interpretation, has been favored in many real world applications. However noisy values commonly exist in high-speed data streams, e.g. real-time online data feeds that are prone to interference. When processing big data, it is hard to implement pre-processing and sampling in full batches. -
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CrispI
A hybrid graph database with analysis
...For example, using an underlying oodb, a OneToMany and ManyToOne relationships can be implemented allowing quick and robust hierarchies to be built (a subset of a graph). The system also includes a Big Data implementation, other analytics and visualization. The current invokation is based on a Versant Db. Examples for use can be found in CrispI-Examples. -
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deshang
Software to support deshang research
Deshang research project mainly focus on collecting students' behaviors and using big data technologies to analyze the factors which might make effects on behavior changing and to build strategies set of parents and teacher guiding. This SF project aims to provide interface and backend analysis functionalities for project Deshang. The softwares used are WAMP (Window Apache + MySQL + PHP) with phpMyAdmin (web base MySQL admin console) included, WordPress (3.8.1 chinese version), Sphinx as search engine and libMMSeg chinese directionary for Sphinx. -
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Big Sack
Big Sack: A lightweight Java Key/Value store with undo and disk cache.
Big Sack is a Java persistence mechanism that allows storage of key value pairs following the popular Big Data paradigms. Its a very simple and straightforward way to bridge the gap between in-memory data structures and long-term storage. It has the convenience of Java SDK TreeMap and TreeSet classes and is used the same easy way, but it includes rollback through undo logging to checkpoint data so it does not wind up in an unknown state regardless of failures. ... -
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Oblivious Bloom Intersection
Oblivious Bloom Intersection
This page is about the PSI implementation described in the paper: When Private Set Intersection Meets Big Data: An Efficient and Scalable Protocol (CCS 2013). -
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rocsy
Routines for the ocean carbonate system
...The rocsy package is designed for users with some programming experience, preferably in Fortran or python. Others may well prefer the facility of packages such as the Excel version of CO2sys. But rocsy is computationally much faster, being designed for big data sets and ocean models. For models, rocsy offers improved accuracy by avoiding 3 common approximations. Computed variables generally agree with those from CO2sys within 0.005% (Orr and Epitalon, 2013). -
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mrocs
Model routines for the ocean carbonate system
...The mrocs package is designed for users with some programming experience, either in Fortran or python. Others would will prefer the facility of packages such as the Excel version of CO2sys. Because mrocs is computationally much faster, it is suited for big data and ocean models. For models, mrocs offers improved accuracy by avoiding 3 common approximations. Its computed variables generally agree with those from CO2sys within 0.005% (Orr and Epitalon, 2013).