Searching: "learning" in the DMelt project

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  1. Java API Java API: jhpro.nnet.BackpropagationNet class [31%] ..ckpropagation is a supervised learning algorithm and is mainly used ..
  2. Java API Java API: org.encog.neural.networks.training.propagation.back.Backpropagation class [30%] ..terfaces: mltrain, batchsize, learningrate, momentum, gradientworker..
  3. Java API Java API: org.encog.ml.hmm.train.bw.BaseBaumWelch class [29%] ..implementation for baum-welch learning for hmm's. there are currentl..
  4. Java API Java API: org.neuroph.nnet.learning.ResilientPropagation class [29%] ..org.neuroph.nnet.learning class resilientpropagation ja..
  5. Java API Java API: cc.mallet.classify package [28%]
  6. Java API Java API: jhpro.nnet.jknnl.LearningDataModel interface [28%] ..jhpro.nnet.jknnl interface learningdatamodel all known implementi..
  7. Java API Java API: jhpro.nnet.jknnl.LearningFactorFunctionalModel interface [28%] ..jhpro.nnet.jknnl interface learningfactorfunctionalmodel all know..
  8. Java API Java API: jhpro.nnet package [28%]
  9. Java API Java API: org.encog.ml.CalculateScore interface [28%] ..ulate the score for a machine learning method. this allows networks ..
  10. Java API Java API: org.encog.ml.MLClustering interface [28%] ..ingextends mlmethod a machine learning method that is used to break ..
  11. Java API Java API: org.encog.ml.MLEncodable interface [28%] ..ds mlmethod defines a machine learning method that can be encoded to..
  12. Java API Java API: org.encog.ml.MLInput interface [28%] ..f double values. many machine learning methods, such as neural netwo..
  13. Java API Java API: org.encog.ml.MLInputOutput interface [28%] ..f double values. many machine learning methods, such as neural netwo..
  14. Java API Java API: org.encog.ml.MLOutput interface [28%] ..f double values. many machine learning methods, such as neural netwo..
  15. Java API Java API: org.encog.ml.MLRegression interface [28%] ..inputoutput defines a machine learning method that supports regressi..
  16. Java API Java API: org.encog.ml.data.MLDataError class [28%] ..exception used by the machine learning methods classes to indicate a..
  17. Java API Java API: org.encog.ml.factory.MLMethodFactory class [28%] ..ory is used to create machine learning methods. field summary fields..
  18. Java API Java API: org.encog.ml.train.MLTrain interface [28%] ..training method for a machine learning method. most mlmethod objects..
  19. Java API Java API: org.neuroph.core.events.LearningEventListener interface [28%] ..neuroph.core.events interface learningeventlistener all superinterfa..
  20. Java API Java API: org.neuroph.core.learning.error.ErrorFunction interface [28%] ..org.neuroph.core.learning.error interface errorfunction..
  21. Java API Java API: org.neuroph.nnet.learning.BinaryHebbianLearning class [28%] ..org.neuroph.nnet.learning class binaryhebbianlearning j..
  22. Java API Java API: org.neuroph.nnet.learning.InstarLearning class [28%] ..org.neuroph.nnet.learning class instarlearning java.lan..
  23. Java API Java API: org.neuroph.nnet.learning.OutstarLearning class [28%] ..org.neuroph.nnet.learning class outstarlearning java.la..
  24. Java API Java API: jhpro.nnet.jknnl.WTMLearningFunctionWithTired class [27%] ..jhpro.nnet.jknnl class wtmlearningfunctionwithtired java.lang.ob..
  25. Java API Java API: org.apache.commons.math3.ml.neuralnet.sofm.LearningFactorFunctionFactory class [27%] ..math3.ml.neuralnet.sofm class learningfactorfunctionfactory java.lan..
  26. Java API Java API: org.encog.app.analyst.commands.CmdEvaluate class [27%] ..is used to evaluate a machine learning method. evaluation data is pr..
  27. Java API Java API: org.encog.app.analyst.commands.CmdEvaluateRaw class [27%] ..is used to evaluate a machine learning method. evaluation data is pr..
  28. Java API Java API: cc.mallet.types package [26%]
  29. Java API Java API: org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation class [26%] ..terfaces: mltrain, batchsize, learningrate, gradientworkerowner, tra..
  30. Java API Java API: org.encog.ml.bayesian.training.TrainBayesian class [24%] .. get the current best machine learning method from the training. bay..
  31. Java API Java API: org.encog.ml.genetic.MLMethodGeneticAlgorithm class [24%] .. get the current best machine learning method from the training. int..
  32. Java API Java API: org.joone.engine.Monitor class [24%] ..et the parameters of the net (learning rate, momentum, ecc.). each c..
  33. Wiki Wiki: http://jwork.org/wiki/DMelt:AI/3 Kohonen Maps [24%] ..is trained using unsupervised learning to produce a two-dimensional ..
  34. Jython Jython example: neural_net_kohenmap1.py [24%] ..trix(inputsize, 3); kfm.setmaxlearningcycles(maxcycle); kfm.createma..
  35. Java API Java API: jhpro.nnet.jknnl.WTALearningFunctionWithTired class [24%] ..jhpro.nnet.jknnl class wtalearningfunctionwithtired java.lang.ob..
  36. Java API Java API: org.encog.app.analyst.commands.CmdCreate class [24%] ..d is used to create a machine learning method. field summary fields"..
  37. Java API Java API: org.encog.app.analyst.commands.CmdTrain class [24%] ..perform training on a machine learning method and dataset. field sum..
  38. Java API Java API: org.encog.ml.train.strategy.Strategy interface [24%] ..strategy, resetstrategy, smartlearningrate, smartmomentum, stoppings..
  39. Java API Java API: org.joone.util.DynamicAnnealing class [24%] ..in controls the change of the learning rate based on the difference ..
  40. Java API Java API: org.neuroph.contrib.RecommenderNetwork class [24%] ..ural network based on hebbian learning. still under development, mos..
  41. Java API Java API: org.neuroph.nnet.Adaline class [24%] ..network architecture with lms learning rule. uses bias input, bipola..
  42. Java API Java API: org.neuroph.nnet.CompetitiveNetwork class [24%] ..ural network with competitive learning rule. see also: serialized fo..
  43. Java API Java API: org.neuroph.nnet.ElmanNetwork class [24%] ..ralnetwork under development: learning rule backprop through time re..
  44. Java API Java API: org.neuroph.nnet.Instar class [24%] ..ar neural network with instar learning rule. see also: serialized fo..
  45. Java API Java API: org.neuroph.nnet.JordanNetwork class [24%] ..ralnetwork under development: learning rule backprop through time re..
  46. Java API Java API: org.neuroph.nnet.MaxNet class [24%] ..ural network with competitive learning rule. see also: serialized fo..
  47. Java API Java API: org.neuroph.nnet.Outstar class [24%] ..r neural network with outstar learning rule. see also: serialized fo..
  48. Java API Java API: org.neuroph.nnet.learning.HopfieldLearning class [24%] ..org.neuroph.nnet.learning class hopfieldlearning java.l..
  49. Java API Java API: org.neuroph.nnet.learning.RBFLearning class [24%] ..org.neuroph.nnet.learning class rbflearning java.lang.o..
  50. Java API Java API: org.neuroph.nnet.learning.SigmoidDeltaRule class [24%] ..org.neuroph.nnet.learning class sigmoiddeltarule java.l..
  51. Java API Java API: org.neuroph.nnet.learning.SupervisedHebbianLearning class [24%] ..org.neuroph.nnet.learning class supervisedhebbianlearni..
  52. Java API Java API: org.neuroph.samples.XorResilientPropagationSample class [24%] ..k using resilient propagation learning rule for the xor problem. con..
  53. Java API Java API: org.neuroph.samples package [24%]
  54. Java API Java API: org.neuroph.util.random.NguyenWidrowRandomizer class [24%] ..th back propagation family of learning rules. based on nguyenwidrowr..
  55. Java API Java API: boofcv.alg.tracker.tld.TldTracker class [20%] ..bject main class for tracking-learning-detection (tld) [1] (a.k.a pr..
  56. Java API Java API: org.encog.ml.data.basic.BasicMLComplexData class [20%] ..with nearly any encog machine learning method. however, not all enco..
  57. Java API Java API: org.encog.ml.svm.training.SVMSearchTrain class [20%] .. get the current best machine learning method from the training. boo..
  58. Java API Java API: org.encog.neural.networks.training.lma.LevenbergMarquardtTraining class [20%] ..ot.com/2009/11/neural-network-learning-by-levenberg_18.html http://m..
  59. Java API Java API: org.encog.neural.networks.training.pnn.TrainBasicPNN class [20%] .. get the current best machine learning method from the training. dou..
  60. Java API Java API: org.encog.ml.data.MLDataSet interface [20%] ..ct classes that store machine learning data. this interface is desig..
  61. Java API Java API: org.joone.engine.BiasedLinearLayer class [20%] ..ong with their biases. in the learning process the biases are adjust..
  62. Java API Java API: org.joone.util package [20%]
  63. Java API Java API: org.neuroph.core.data.DataSetRow class [20%] ..desired output for supervised learning rules. it can also be used on..
  64. Jython Jython example: neural_net_kohonen_map2D.py [19%] ..trix(inputsize, 2); kfm.setmaxlearningcycles(maxcycle); kfm.createma..
  65. Java Java example: neural_net_MLP_RT.java [19%] ..trow; import org.neuroph.core.learning.supervisedlearning; import or..
  66. Jython Jython example: neural_net_kohonen_mapND.py [19%] ..w(pn.getp1d(0,1)) filedata = learningdata(pn) learning = wtalearnin..
  67. Jython Jython example: neural_net_kohonen_map3D.py [19%] ..trix(inputsize, 3); kfm.setmaxlearningcycles(maxcycle); kfm.createma..
  68. Java API Java API: ca.pfv.spmf.algorithms.sequential_rules.rulegen.AlgoRuleGen class [19%] ..nt se-quences,\xc2\x94machine learning, vol. 42, no.1-2, pp. 31-60, ..
  69. Java API Java API: cc.mallet.classify.AdaBoost class [19%] .. boosting approach to machine learning: an overview." in msri worksh..
  70. Java API Java API: cc.mallet.classify.AdaBoostM2 class [19%] ..orithm" in journal of machine learning: proceedings of the 13th inte..
  71. Java API Java API: cc.mallet.classify.AdaBoostM2Trainer class [19%] ..orithm" in journal of machine learning: proceedings of the 13th inte..
  72. Java API Java API: cc.mallet.classify.AdaBoostTrainer class [19%] ..tic generalization of on-line learning and an application to boostin..
  73. Java API Java API: cc.mallet.fst.semi_supervised.GELattice class [19%] .. criteria for semi-supervised learning of conditional random fields"..
  74. Java API Java API: cc.mallet.topics.PAM4L class [19%] .. pachinko allocation with mle learning, based on andrew's latent dir..
  75. Java API Java API: cc.mallet.topics package [19%]
  76. Java API Java API: cc.mallet.types.BiNormalSeparation class [19%] ..ge forman, journal of machine learning research, 3:1289--1305, 2003...
  77. Java API Java API: jhpro.nnet.WeightMatrix class [19%] .. are changed during the net's learning process. each neural net has ..
  78. Java API Java API: jhpro.nnet.jknnl.LearningData class [19%] ..jhpro.nnet.jknnl class learningdata java.lang.object jhpro.nn..
  79. Java API Java API: org.encog.mathutil.randomize.RandomChoice class [19%] ..d a roulette wheel in machine learning texts. how it differs from a ..
  80. Java API Java API: org.encog.ml.MLProperties interface [19%] ..ds mlmethod defines a machine learning method that holds properties...

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