Quantum Machine Learning Classifier
Quantum Machine Learning Classifier
复制标题
量子机器学习分类器
DOI：
10.1007/978-3-030-98012-2_34
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Mosley, Pauline
中科院分区：
文献类型：
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作者：
Leider, Avery;Jaoude, Gio Abou;Strobel, Abigail E.;Mosley, Pauline
这个量子机器学习分类器（QMLC）在深度神经网络中使用量子计算的数学，利用SciKit-Learn数据集“Iris”来查找和分类三种不同的鸢尾花物种的特定花类型：Versicolor，Setosa和Virginica。在该数据集中，每种虹膜类型有四个特征：花瓣长度，花瓣宽度，萼片长度和萼片宽度。量子计算机器学习分类器优于经典的深度学习神经网络方法。重要的是，该分类器在更少的时期内训练。
This Quantum Machine Learning Classifier (QMLC) uses the mathematics of quantum computing in a deep neural network to find and classify the specific flower type of the three different iris flower species: Versicolor, Setosa and Virginica, utilizing the SciKit-Learn dataset “Iris.” In that dataset, there are four characteristic features of each iris type: petal length, petal width, sepal length, and sepal width. The quantum computing machine learning classifier out-performed the classical deep learning neural network methods. Significant is that this classifier trained in fewer epochs.