| Abstrakt: |
In this work, we present our experiment's results where we simulate the quantum amplitude amplification algorithm for a prediction problem. The problem is to calculate the total probability of a good class by an ensemble model. Theoretically, the quantum prediction will be quadratically faster than a classical prediction. We need to get outputs (probabilities of the good class) of all classifiers. After that, by summation the probabilities the ensemble model returns the total probability of the good class for an input object. Let us demonstrate how the quantum amplitude amplification algorithm allows us to estimate the total probability. In this experiment, we count an iterations number of quantum search running to estimate the total probability. [ABSTRACT FROM AUTHOR] |
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