forked from kscience/kmath
example fixed
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@ -163,7 +163,7 @@ class NeuralNetwork(private val layers: List<Layer>) {
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for ((xBatch, yBatch) in iterBatch(xTrain, yTrain)) {
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train(xBatch, yBatch)
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}
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println("Accuracy:${accuracy(yTrain, predict(xTrain).argMax(1, true))}")
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println("Accuracy:${accuracy(yTrain, predict(xTrain).argMax(1, true).asDouble())}")
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}
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}
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@ -230,7 +230,7 @@ fun main() = BroadcastDoubleTensorAlgebra {
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val prediction = model.predict(xTest)
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// process raw prediction via argMax
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val predictionLabels = prediction.argMax(1, true)
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val predictionLabels = prediction.argMax(1, true).asDouble()
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// find out accuracy
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val acc = accuracy(yTest, predictionLabels)
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