Found in titles:
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Wiki: Java.Network.Launching.Protocol
[100%] [Java specification requests]
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DMelt: Catalano.Graph.Network.ClosenessCentrality [100%] (Java API)
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DMelt: Catalano.Graph.Network.DegreeCentrality [100%] (Java API)
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DMelt: Catalano.Graph.Network.EigenvectorCentrality [100%] (Java API)
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DMelt: Catalano.Graph.Network.Hits [100%] (Java API)
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DMelt: Catalano.Graph.Network.PageRank [100%] (Java API)
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DMelt: Catalano.Graph.Network.package-frame [100%] (Java API)
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DMelt: Catalano.Graph.Network.package-summary [100%] (Java API)
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DMelt: edu.rit.clu.network.FloydClu [87%] (Java API)
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DMelt: edu.rit.clu.network.FloydPrint [87%] (Java API)
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DMelt: edu.rit.clu.network.FloydRandom [87%] (Java API)
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DMelt: edu.rit.clu.network.FloydSeq [87%] (Java API)
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DMelt: edu.rit.clu.network.package-frame [87%] (Java API)
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DMelt: edu.rit.clu.network.package-summary [87%] (Java API)
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DMelt: edu.rit.hyb.network.FloydHyb [87%] (Java API)
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DMelt: edu.rit.hyb.network.FloydPrint [87%] (Java API)
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DMelt: edu.rit.hyb.network.FloydRandom [87%] (Java API)
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DMelt: edu.rit.hyb.network.FloydSeq [87%] (Java API)
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DMelt: edu.rit.hyb.network.package-frame [87%] (Java API)
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DMelt: edu.rit.hyb.network.package-summary [87%] (Java API)
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DMelt: edu.rit.smp.network.FloydPrint [87%] (Java API)
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DMelt: edu.rit.smp.network.FloydRandom [87%] (Java API)
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DMelt: edu.rit.smp.network.FloydSeq [87%] (Java API)
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DMelt: edu.rit.smp.network.FloydSmpCol [87%] (Java API)
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DMelt: edu.rit.smp.network.FloydSmpRow [87%] (Java API)
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DMelt: edu.rit.smp.network.package-frame [87%] (Java API)
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DMelt: edu.rit.smp.network.package-summary [87%] (Java API)
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DMelt: org.apache.commons.math3.ml.neuralnet.Network [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationBiPolar [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationBipolarSteepenedSigmoid [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationClippedLinear [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationCompetitive [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationElliott [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationElliottSymmetric [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationFunction [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationGaussian [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationLOG [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationLinear [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationRamp [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationReLU [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationSIN [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationSigmoid [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationSoftMax [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationSteepenedSigmoid [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationStep [75%] (Java API)
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DMelt: org.encog.engine.network.activation.ActivationTANH [75%] (Java API)
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DMelt: org.encog.engine.network.activation.package-frame [75%] (Java API)
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DMelt: org.encog.engine.network.activation.package-summary [75%] (Java API)
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Jython Example: neural_net_analysis.py [62%] Backpropogation neural network training/analysis
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Jython Example: neural_net_bpnn.py [62%] Back-Propagation Neural Network implemented in Python
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Java Example: joone_TimeSeries.java [62%] Neural Network with Joone for TimeSeries forecasting
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Jython Example: recurn_lstm1.py [62%] Recurrent Neural Network (LSTM)
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Jython Example: classify_neuralnet.py [62%] Classification using Multilayer Perceptron Neural Network
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Jython Example: bayes_rain.py [62%] Bayesian network for rain predictions
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DMelt: org.apache.commons.math3.ml.neuralnet.Network.NeuronIdentifierComparator [62%] (Java API)
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Java Example: neural_net_bayesian_k2.java [50%] Bayesian network using Encog Java and simpel logic
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Jython Example: neural_net_2.py [50%] Backpropagation neural net (2): Create a neural network
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Java Example: joone_XOR.java [50%] Neural network using Joone for solving XOR problem
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Java Example: joone_XORMemory.java [50%] Demonstrate Neural Network using Joone with InMemory arrays
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Jython Example: joone_timeseries.py [50%] Forecasting time series using Joone neural network
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Java Example: neural_net_MLP_RT.java [50%] Multi Layer Perceptron network using Resilient Propagation
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Jython Example: classify_neural_net_plot.py [50%] Classify data with neural network with many input layers
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Jython Example: javacnn1.py [50%] Convolutional neural network for 28x28 px and its prediction
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Jython Example: neural_net_jayes1.py [50%] Bayesian network using jayes Java library
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Jython Example: neural_net_jayes3.py [50%] Bayesian network using using the Jayes library
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Jython Example: neural_net_jayes2.py [50%] Bayesian network using using the Jayes library
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