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mulan

于 2020-12-17 发布 文件大小:976KB
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代码说明：

  mulan实现多标签分类，内含多个重要的分类器，乃是分类中的精华(Mulan implementation of multi label classification, containing multiple important classifier, is the essence of the classification)

文件列表：

mulan
.....\.classpath,592,2015-08-04
.....\.project,381,2015-07-17
.....\bin
.....\...\emotions.arff,380476,2012-07-26
.....\...\emotions.xml,332,2012-07-26
.....\...\mlknn
.....\...\.....\Main.class,2023,2015-08-07
.....\...\.....\NewMlknn.class,8959,2015-08-10
.....\...\mulan
.....\...\.....\classifier
.....\...\.....\..........\InvalidDataException.class,638,2015-08-04
.....\...\.....\..........\lazy
.....\...\.....\..........\....\BRkNN$ExtensionType.class,1228,2015-08-04
.....\...\.....\..........\....\BRkNN.class,9309,2015-08-04
.....\...\.....\..........\....\IBLR_ML.class,6982,2015-08-04
.....\...\.....\..........\....\MLkNN.class,6547,2015-08-04
.....\...\.....\..........\....\MultiLabelKNN.class,2697,2015-08-11
.....\...\.....\..........\LearnerException.class,625,2015-08-04
.....\...\.....\..........\meta
.....\...\.....\..........\....\ClusteringBased.class,5471,2015-08-04
.....\...\.....\..........\....\ConstrainedKMeans$bucketInstance.class,1246,2015-08-04
.....\...\.....\..........\....\ConstrainedKMeans.class,12102,2015-08-04
.....\...\.....\..........\....\EnsembleOfSubsetLearners$IdComparator.class,1425,2015-08-04
.....\...\.....\..........\....\EnsembleOfSubsetLearners$LabelSubsetsWeight.class,2024,2015-08-04
.....\...\.....\..........\....\EnsembleOfSubsetLearners$SubsetsDistance.class,1956,2015-08-04
.....\...\.....\..........\....\EnsembleOfSubsetLearners.class,19559,2015-08-04
.....\...\.....\..........\....\HierarchyBuilder$Method.class,1289,2015-08-04
.....\...\.....\..........\....\HierarchyBuilder.class,14388,2015-08-04
.....\...\.....\..........\....\HMC.class,12965,2015-08-04
.....\...\.....\..........\....\HMCNode.class,3905,2015-08-04
.....\...\.....\..........\....\HOMER.class,6047,2015-08-04
.....\...\.....\..........\....\MultiLabelMetaLearner.class,783,2015-08-04
.....\...\.....\..........\....\RAkEL.class,7688,2015-08-04
.....\...\.....\..........\....\RAkELd.class,7078,2015-08-04
.....\...\.....\..........\....\SubsetLearner.class,14140,2015-08-04
.....\...\.....\..........\....\thresholding
.....\...\.....\..........\....\............\ExampleBasedFMeasureOptimizer.class,4345,2015-08-04
.....\...\.....\..........\....\............\Meta.class,6343,2015-08-04
.....\...\.....\..........\....\............\MetaLabeler.class,8911,2015-08-04
.....\...\.....\..........\....\............\MLPTO.class,7206,2015-08-04
.....\...\.....\..........\....\............\OneThreshold.class,8163,2015-08-04
.....\...\.....\..........\....\............\RCut.class,7500,2015-08-04
.....\...\.....\..........\....\............\SCut.class,8253,2015-08-04
.....\...\.....\..........\....\............\ThresholdPrediction.class,7430,2015-08-04
.....\...\.....\..........\ModelInitializationException.class,662,2015-08-04
.....\...\.....\..........\MultiLabelLearner.class,553,2015-08-04
.....\...\.....\..........\MultiLabelLearnerBase.class,2826,2015-08-04
.....\...\.....\..........\MultiLabelOutput.class,3841,2015-08-04
.....\...\.....\..........\neural
.....\...\.....\..........\......\BPMLL.class,13580,2015-08-04
.....\...\.....\..........\......\BPMLLAlgorithm.class,7512,2015-08-04
.....\...\.....\..........\......\DataPair.class,3092,2015-08-04
.....\...\.....\..........\......\MMPLearner.class,11988,2015-08-04
.....\...\.....\..........\......\MMPMaxUpdateRule.class,1471,2015-08-04
.....\...\.....\..........\......\MMPRandomizedUpdateRule.class,2979,2015-08-04
.....\...\.....\..........\......\MMPUniformUpdateRule.class,2257,2015-08-04
.....\...\.....\..........\......\MMPUpdateRuleBase.class,2674,2015-08-04
.....\...\.....\..........\......\MMPUpdateRuleType.class,1186,2015-08-04
.....\...\.....\..........\......\model
.....\...\.....\..........\......\.....\ActivationFunction.class,454,2015-08-04
.....\...\.....\..........\......\.....\ActivationLinear.class,924,2015-08-04
.....\...\.....\..........\......\.....\ActivationTANH.class,921,2015-08-04
.....\...\.....\..........\......\.....\BasicNeuralNet.class,4840,2015-08-04
.....\...\.....\..........\......\.....\NeuralNet.class,421,2015-08-04
.....\...\.....\..........\......\.....\Neuron.class,5100,2015-08-04
.....\...\.....\..........\......\ModelUpdateRule.class,321,2015-08-04
.....\...\.....\..........\......\NormalizationFilter.class,3682,2015-08-04
.....\...\.....\..........\......\ThresholdFunction.class,2833,2015-08-04
.....\...\.....\..........\transformation
.....\...\.....\..........\..............\AdaBoostMH.class,1851,2015-08-04
.....\...\.....\..........\..............\BinaryRelevance.class,3519,2015-08-04
.....\...\.....\..........\..............\CalibratedLabelRanking.class,10108,2015-08-04
.....\...\.....\..........\..............\ClassifierChain.class,5590,2015-08-04
.....\...\.....\..........\..............\EnsembleOfClassifierChains.class,6300,2015-08-04
.....\...\.....\..........\..............\EnsembleOfPrunedSets.class,5592,2015-08-04
.....\...\.....\..........\..............\IncludeLabelsClassifier.class,2715,2015-08-04
.....\...\.....\..........\..............\LabelPowerset.class,5025,2015-08-04
.....\...\.....\..........\..............\LabelsetPruning.class,3834,2015-08-04
.....\...\.....\..........\..............\MultiClassLearner.class,2215,2015-08-04
.....\...\.....\..........\..............\MultiLabelStacking.class,16409,2015-08-04
.....\...\.....\..........\..............\PPT$Strategy.class,1219,2015-08-04
.....\...\.....\..........\..............\PPT.class,5943,2015-08-04
.....\...\.....\..........\..............\PrunedSets$Strategy.class,1242,2015-08-04
.....\...\.....\..........\..............\PrunedSets.class,6820,2015-08-04
.....\...\.....\..........\..............\TransformationBasedMultiLabelLearner.class,2291,2015-08-04
.....\...\.....\core
.....\...\.....\....\ArgumentNullException.class,1216,2015-08-04
.....\...\.....\....\MulanException.class,594,2015-08-04
.....\...\.....\....\MulanJavadoc.class,3615,2015-08-04
.....\...\.....\....\MulanRuntimeException.class,622,2015-08-04
.....\...\.....\....\Util.class,1104,2015-08-04
.....\...\.....\....\WekaException.class,604,2015-08-04
.....\...\.....\data
.....\...\.....\....\ConditionalDependenceIdentifier.class,8602,2015-08-04
.....\...\.....\....\ConverterCLUS.class,5825,2015-08-04
.....\...\.....\....\ConverterLibSVM.class,6687,2015-08-04
.....\...\.....\....\DataLoadException.class,616,2015-08-04
.....\...\.....\....\DataUtils.class,1281,2015-08-04
.....\...\.....\....\GreedyLabelClustering.class,8137,2015-08-04

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  • Desktop2
    电机的仿真，运用simulink对电机进行分块建模仿真，得出电机的转速和转矩的图像(The simulation using simulink motor on the motor, it is concluded that the partitioned modeling simulation of motor speed and torque images)
    2011-05-28 19:35:02下载
    积分：1
  • Multipath
    1.AWGN条件下QPSK、16QAM、64QAM的仿真；2.单径及多径瑞利信道下三种调制的仿真；3.100MHz多径莱斯信道下三种调制的仿真；4.100MHz多径信道下三种调制的Matched Filter Bound(MFB)仿真(1. Under the condition of AWGN QPSK, 16 qam and 64 qam simulation 2. Single diameter and multipath Rayleigh channel under three kinds of modulation simulation 3.100 MHz channel multipath rice, under three kinds of modulation simulation 4.100 MHz multipath channel under three kinds of modulation Matched Filter Bound (MFB) simulation)
    2014-09-03 23:58:59下载
    积分：1
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    Antoine equation from thermodynamic applications in chemicl engineering
    2014-09-12 17:00:23下载
    积分：1
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    ofdm调制的matlab程序实现，经过验证是可以实现的，但是具体应用的时候需要自行修改程序中的一些参数(ofdm modulation matlab program, after verification can be achieved, but it requires its own specific application to modify some of the parameters in the program)
    2013-11-08 10:10:06下载
    积分：1
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    2015-01-15 14:12:44下载
    积分：1
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    仿真了跳频系统中并行捕获的性能，希望对大家有帮助(parallel acquisition )
    2010-06-24 10:27:35下载
    积分：1
  • LTEdetail
    LTE的详细讲解，对于OFDM等进行了讲解，对于LTE初学者有很大的帮助。(LTE detailed explanations, for OFDM, etc. were explained, the LTE is very helpful for beginners.)
    2010-08-19 22:12:51下载
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    Structural instability study of laminated composite plates due to fluid structure interaction
    2012-01-16 18:17:48下载
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    本例是一个用PIC16F73编写的门禁读卡器解码并显示的源程序(This case is a PIC16F73 prepared to use access control card reader and display the source decoder)
    2008-01-04 17:15:49下载
    积分：1
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    matlab 信息处理设计 fir滤波器设计(Information processing design fir filter design)
    2009-11-04 15:12:27下载
    积分：1
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