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  • The paper is oriented to statistical testing of ANN output. The neural network with several inputs and single output is able to classify objects into two classes depending on the ANN output value. Various statistical properties of ANN output signal enforce various strategies of statistical testing. The testing principles are demonstrated on the biomedical data analysis. All the calculations were performed in the Matlab environment.
  • The paper is oriented to statistical testing of ANN output. The neural network with several inputs and single output is able to classify objects into two classes depending on the ANN output value. Various statistical properties of ANN output signal enforce various strategies of statistical testing. The testing principles are demonstrated on the biomedical data analysis. All the calculations were performed in the Matlab environment. (en)
  • Článek je orientován na statistické testování výstupu ANN. Neuronová síť s několika vstupy a jedním výstupem je schopná klasifikovat objekty do dvou tříd podle hodnoty výstupu ANN. Statistické vlastnosti výstupu ANN podmiňují různé strategie statistického testování. Principy testování jsou demonstrovány na analýze biomedicínských dat. Všechny výpočty byly realizovány v prostředí Matlab. (cs)
Title
  • Statistical Properties of ANN Output
  • Statistical Properties of ANN Output (en)
  • Statistické vlastnosti výstupu ANN (cs)
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  • Statistical Properties of ANN Output
  • Statistical Properties of ANN Output (en)
  • Statistické vlastnosti výstupu ANN (cs)
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  • RIV/60461373:22340/05:00014379!RIV06-MSM-22340___
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  • 544542
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  • RIV/60461373:22340/05:00014379
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  • ANN; hypothesis; statistical testing; classification; biomedical research; multiple sclerosis; Matlab (en)
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  • [7B7E0D61CAF2]
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  • Bartoš, Aleš
  • Kukal, Jaromír
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  • 22340
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