文件名称:Shark-3.0.0
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [C/C++] [源码]
- 上传时间：
- 2016-09-21
- 文件大小：
- 14.09mb
- 下载次数：
- 0次
- 提 供 者：
- 陈*
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
SHARK是一种快速、模块化、功能丰富的开源C++机器学习库。它提供了线性和非线性优化的方法，基于内核的学习算法，神经网络，和其他各种机器学习技术（见下面的特征列表）。它作为一个强大的工具箱，已经在现实世界有很多应用和研究。SHARK依赖于Boost和 cmake。它兼容Windows，Solaris，MacOS X和Linux。根据GNU通用公共许可证授权许可。-SHARK is a fast, modular, feature-rich open-source C++ machine learning library. It provides methods for linear and nonlinear optimization, kernel-based learning algorithms, neural networks, and various other machine learning techniques (see the feature list below). It serves as a powerful toolbox for real world applications as well as research. Shark depends on Boost and CMake. It is compatible with Windows, Solaris, MacOS X, and Linux. Shark is licensed under the permissive GNU Lesser General Public License.
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下载文件列表
Shark-3.0.0
...........\.gitignore
...........\CMakeLists.txt
...........\COPYING
...........\COPYING.LESSER
...........\CTestConfig.cmake
...........\README.txt
...........\SharkConfig.cmake.in
...........\SharkConfigVersion.cmake.in
...........\Test
...........\....\Algorithms
...........\....\..........\DirectSearch
...........\....\..........\............\CMA.cpp
...........\....\..........\............\CMSA.cpp
...........\....\..........\............\ElitistCMA.cpp
...........\....\..........\............\FastNonDominatedSort.cpp
...........\....\..........\............\Indicators
...........\....\..........\............\..........\HypervolumeIndicator.cpp
...........\....\..........\............\MOCMA.cpp
...........\....\..........\............\Operators
...........\....\..........\............\.........\Mutation
...........\....\..........\............\.........\........\BitflipMutation.cpp
...........\....\..........\............\.........\PenalizingEvaluator.cpp
...........\....\..........\............\.........\Selection
...........\....\..........\............\.........\.........\IndicatorBasedSelection.cpp
...........\....\..........\............\.........\.........\Selection.cpp
...........\....\..........\............\ParetoDominanceComparator.cpp
...........\....\..........\............\RealCodedNSGAII.cpp
...........\....\..........\............\SimplexDownhill.cpp
...........\....\..........\............\SteadyStateMOCMA.cpp
...........\....\..........\............\VDCMA.cpp
...........\....\..........\GradientDescent
...........\....\..........\...............\BFGS.cpp
...........\....\..........\...............\CG.cpp
...........\....\..........\...............\LBFGS.cpp
...........\....\..........\...............\LineSearch.cpp
...........\....\..........\...............\NoisyRprop.cpp
...........\....\..........\...............\Rprop.cpp
...........\....\..........\...............\SteepestDescent.cpp
...........\....\..........\...............\TrustRegionNewton.cpp
...........\....\..........\GridSearch.cpp
...........\....\..........\Hypervolume.cpp
...........\....\..........\JaakkolaHeuristic.cpp
...........\....\..........\KMeans.cpp
...........\....\..........\LP
...........\....\..........\..\LinearProgram.cpp
...........\....\..........\Trainers
...........\....\..........\........\Budgeted
...........\....\..........\........\........\AbstractBudgetMaintenanceStrategy_Test.cpp
...........\....\..........\........\........\KernelBudgetedSGDTrainer_Test.cpp
...........\....\..........\........\........\MergeBudgetMaintenanceStrategy_Test.cpp
...........\....\..........\........\........\RemoveBudgetMaintenanceStrategy_Test.cpp
...........\....\..........\........\CSvmTrainer.cpp
...........\....\..........\........\EpsilonSvmTrainer.cpp
...........\....\..........\........\FisherLDA.cpp
...........\....\..........\........\KernelMeanClassifier.cpp
...........\....\..........\........\KernelNormalization.cpp
...........\....\..........\........\LDA.cpp
...........\....\..........\........\LinearRegression.cpp
...........\....\..........\........\LinearSvmTrainer.cpp
...........\....\..........\........\McSvmTrainer.cpp
...........\....\..........\........\MissingFeatureSvmTrainerTests.cpp
...........\....\..........\........\NBClassifierTrainerTests.cpp
...........\....\..........\........\Normalization.cpp
...........\....\..........\........\OneClassSvmTrainer.cpp
...........\....\..........\........\PCA.cpp
...........\....\..........\........\Perceptron.cpp
...........\....\..........\........\RegularizationNetworkTrainer.cpp
...........\....\..........\........\SigmoidFit.cpp
...........\....\..........\nearestneighbors.cpp
...........\....\..........\testFunction.h
...........\....\CMakeLists.txt
...........\....\Core
...........\....\....\Iterators.cpp
...........\....\....\Math.cpp
...........\....\....\ScopedHandleTests.cpp
...........\....\Data
...........\....\....\Bootstrap.cpp
...........\....\....\CVDatasetTools.cpp
...........\....\....\Csv.cpp
...........\....\....\DataView