Search Results for "data mining algorithms in c#.net"
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Showing 70 open source projects for "data mining algorithms in c#.net"
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AWS Encryption SDK for Java
AWS Encryption SDK
The AWS Encryption SDK is a client-side encryption library designed to make it easy for everyone to encrypt and decrypt data using industry standards and best practices. It enables you to focus on the core functionality of your application, rather than on how to best encrypt and decrypt your data. The AWS Encryption SDK is provided free of charge under the Apache 2.0 license. With the AWS Encryption SDK, you define a master key provider (Java and Python) or a keyring (C, C#/.NET, and JavaScript... -
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Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM languages... -
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CloudI is an open-source private cloud computing framework for efficient, secure, and internal data processing. CloudI provides scaling for previously unscalable source code with efficient fault-tolerant execution of ATS, C/C++, Erlang/Elixir, Go, Haskell, Java, JavaScript/node.js, OCaml, Perl, PHP, Python, Ruby, or Rust services. The bare essentials for efficient fault-tolerant processing on a cloud!
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UnBBayes
Framework & GUI for Bayes Nets and other probabilistic models.
UnBBayes is a probabilistic network framework written in Java. It has both a GUI and an API with inference, sampling, learning and evaluation. It supports Bayesian networks, influence diagrams, MSBN, OOBN, HBN, MEBN/PR-OWL, PRM, structure, parameter and incremental learning. Please, visit our wiki (https://sourceforge.net/p/unbbayes/wiki/Home/) for more information. Check out the license section (https://sourceforge.net/p/unbbayes/wiki/License/) for our licensing policy. -
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Generic data-assimilation toolbox written in java, with native (c and fortran) libraries for high performance computing. Provides tools to couple to your own model and a wide range of algorithms, ranging from parameter calibration to Kalman filters.
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Weka
Machine learning software to solve data mining problems
Weka is a collection of machine learning algorithms for solving real-world data mining problems. It is written in Java and runs on almost any platform. The algorithms can either be applied directly to a dataset or called from your own Java code. -
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The Lemur Project
Search engine and data mining applications and ClueWeb datasets.
The Lemur Project develops search engines, browser toolbars, text analysis tools, and data resources that support research and development of information retrieval and text mining software, including the Indri search engine in C++, the Galago search engine research framework in Java, the RankLib learning to rank library, ClueWeb09 and ClueWeb12 datasets and the Sifaka data mining application. -
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NestProfessor Programmer Edition
Nesting SDK, Library
This is a SDK which can nest/layout the part/geometry/polygon on the material or sheet intelligently, you can get the best utilization of the materials, this SDK also support read/write DXF/DWG files and part-in-part nesting. New nesting lagorithm is implenmented, more good to support true shape part or material. -
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libinstrument (ex libcsdbg)
C/C++ function instrumentation (AOP, exception/stack tracing, GC)
... with IDEs (CLion, Eclipse e.t.c) is straightforward. Using lazy algorithms there is virtually zero overhead in benchmarks and minimum overhead in execution time. Libinstrument tries to be as non-intrusive as possible, while trying to help the developer offering basic reflection. There are Unit Tests for each class and method, testing is driven with CTest. -
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OpenDino
Open Source Java platform for Optimization, DoE, and Learning.
OpenDino is an open source Java platform for optimization, design of experiment and learning. It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules". Implemented Modules Evolutionary Algorithms: - CMA-ES - (1+1)-ES - Differential Evolution Deterministic optimization algorithm: - SIMPLEX Learning: - a simple Artificial Neural Net Optimization problems: - test functions - interface for executing... -
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DSTK - Data Science TooKit 3
Data and Text Mining Software for Everyone
DSTK - Data Science Toolkit 3 is a set of data and text mining softwares, following the CRISP DM model. DSTK offers data understanding using statistical and text analysis, data preparation using normalization and text processing, modeling and evaluation for machine learning and algorithms. It is based on the old version DSTK at https://sourceforge.net/projects/dstk2/ DSTK Engine is like R. DSTK ScriptWriter offers GUI to write DSTK script. DSTK Studio offers SPSS Statistics like GUI... -
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JPPF
The open source grid computing solution
JPPF makes it easy to parallelize computationally intensive tasks and execute them on a Grid. -
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This site hosts the source code for C++ version of the Broker for SBW, NOM module, advanced simulation suite, analysis applications and model editors.
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MYRA
A collection of ACO algorithms for the data mining classification task
MYRA is a collection of Ant Colony Optimization (ACO) algorithms for the data mining classification task. It includes popular rule induction and decision tree induction algorithms. The algorithms are ready to be used from the command line or can be easily called from your own Java code. They are build using a modular architecture, so they can be easily extended to incorporate different procedures and/or use different parameter values. This project is now hosted at: https://github.com/febo... -
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Algorithm Database
Efficient Algorithms implemented in Java
The Aim of this project is to provide a collection of reusable Algorithms which can be used effectively in different scenarios. Algorithm implementations are in Java. Objective here is to implement algorithms which should be more efficient than the JDK implementation and also to create a platform for the researchers who works on Data Mining, Encryption algorithms, ect.. to collaborate and contribute to this project. -
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RDKit
Open-Source Cheminformatics and Machine Learning
A collection of cheminformatics and machine-learning software written in C++ and Python. NOTE: the RDKit source code and downloads are now in github: https://github.com/rdkit/rdkit The core algorithms and data structures are written in C++. Wrappers are provided to use the toolkit from either Python or Java. Additionally, the RDKit distribution includes a PostgreSQL-based cartridge that allows molecules to be stored in relational database and retrieved via substructure and similarity... -
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The Java Data Mining Package (JDMP) is a library that provides methods for analyzing data with the help of machine learning algorithms (e.g. clustering, classification, graphical models, neural networks, Bayesian networks, text processing, optimization).
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smartsbc
Smart Session Border Controller
...: a) Realtime Log file mining module. This subservice module is responsible to analize certain patterns reported in log files in order to detect possible intrusion threats. You can configure your own pattern in your own lof file in order to trigger alerts or take actions. b) Schedule module. This subservice module is responsible to trigger certain action based on cron strategies. c) Plugin module. -
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The c2001 spatio-temporal mining library
An open source spatio-temporal data mining library
Current functions: 1. The General Association Rule Mining Framework(GARMF) library, which support mining association rules from transactions(boolean, weighted, fuzzy), spatial datasets (vector and raster) and spatio-temporal datasets (raster snapshots). Besides it support incremental mining. 2. Rule Filtering Library (RFL), a library for rule evaluation. 3. Besides, DAP-Shell, a GUI shell for GARMF and RFL, will be provided. However I'll pay no more attention on it. -
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scipion-xmipp
Image processing framework to integrate EM software packages.
... into Scipion and contains the algorithms in the core libraries and command line programs. -
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Cenobi
cost estimation and management accounting, using neural networks
Cenobi is designed for management accountants, not (only) for statisticians and data mining experts. Carefully arranged default settings make sure you can concentrate on Cenobi's many accounting features rather than worrying about setting up artificial neural networks or genetic algorithms, which are the main machine learning tools under Cenobi's hood. Cenobi's main benefits are: - ease of use - Utilizing artificial neural networks to estimate cost relationships, Cenobi is able... -
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Graph-RAT is a database abstraction layer designed to make it easy to use a large library of graph-analysis routines on a database as well as add new kinds of algorithms to data mining.
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Schedule Visualization
Tool to visualize and create time-triggered schedules as gant-chart.
The Schedule Visualization tool is based on Eclipse 4 RCP and uses Nebula Gantt charts to visualize schedules. The tool is linked to scheduling and schedule integration algorithms which allow to generate time-triggered schedules and visualizes the calculated schedules. The generated schedule might then be exported to a C header file to update the system schedule. It also supports an online mode using a network monitor to detect if nodes are offline and updates its status in the visualization... -
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cmotif
A method for mining conditional phosphorylation motifs
Phosphorylation motifs represent position-specific amino acid patterns around the phosphorylation sites in the set of phosphopeptides. The discovery of phosphorylation motifs is a very valuable work in bioinformatics. Although several algorithms have been proposed to uncover phosphorylation motifs, the problem of efficiently discovering a set of significant motifs with sufficiently high coverage and non-redundancy still remains unsolved. In this paper, we propose an algorithm called C-Motif... -
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Cost-sensitive Classifiers
Adaboost extensions for cost-sentive classification
Adaboost extensions for cost-sentive classification CSExtension 1 CSExtension 2 CSExtension 3 CSExtension 4 CSExtension 5 AdaCost Boost CostBoost Uboost CostUBoost AdaBoostM1 Implementation of all the listed algorithms of the cluster "cost-sensitive classification". They are the meta algorithms which requires base algorithms e.g. Decision Tree Moreover, Voting criteria is also required e.g. Minimum expected cost criteria Input also requires to load an arff file...
