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casCorMath = new CasCorMathematics(builder.getNetwork()); backPropagation = new BackPropagation(builder.getNetwork()); quickPropagation = new QuickPropagation(builder.getNetwork()); }
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if( kFold>0 ) { trainingData = this.wrapTrainingData(trainingData); } MLTrain train = new QuickPropagation((BasicNetwork) file.getObject(), trainingData, learningRate); if( kFold>0 ) { train = this.wrapTrainer(trainingData,train,kFold); }
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final ParamsHolder holder = new ParamsHolder(args); final double learningRate = holder.getDouble( MLTrainFactory.PROPERTY_LEARNING_RATE, false, 2.0); return new QuickPropagation((BasicNetwork) method, training, learningRate); }