Article Structure
Abstract
In this article, we propose a novel classifier based on quantum computation theory.
Introduction
Taking modern natural science into account, the quantum mechanics theory (QM) is one of the most famous and profound theory which brings a world-shaking revolution for physics.
Basic principle of quantum classifier
As we mentioned in the introduction, the major principle of quantum classifier (QC) is to consider the classifier as a physical system and the whole process of classification as the evolutionary process of a closed quantum system.
Experiment
We tested the performance of QC on two different datasets.
Discussion
We present here our model of text classification and compare it with SVM and KNN on two datasets.
Topics
SVM
Appears in 6 sentences as: SVM (6)
In A Novel Classifier Based on Quantum Computation
- We compared the performance of QC with several classical classification methods, including Support Vector Machine ( SVM ) and K-nearest neighbor (KNN).
Page 3, “Experiment”
- We randomly selected training samples from the training pool ten times to train QC, SVM , and KNN classifier respectively and then verified the three trained classifiers on the testing sets, the results of which are illustrated in Figure 4.
Page 3, “Experiment”
- We noted that the QC performed better than both KNN and SVM on small-scale training sets, when the number of training samples is less than 50.
Page 3, “Experiment”
- Same to the experiment in section 3.1, we randomly selected the training samples from the training pool ten times to train QC, SVM , and KNN classifier respectively and veri fied the models on the testing sets, the results of which are shown in Figure 5.
Page 4, “Experiment”
- We present here our model of text classification and compare it with SVM and KNN on two datasets.
Page 4, “Discussion”
- Moreover, the QC performs well in text classification compared with SVM and KNN and outperforms them on small-scale training sets.
Page 4, “Discussion”
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machine learning
Appears in 4 sentences as: Machine Learning (1) machine learning (3)
In A Novel Classifier Based on Quantum Computation
- Some researchers have employed the principle and technology of quantum computation to improve the studies on Machine Learning (ML) (Aimeur et al., 2006; A'imeur et al., 2007; Chen et al., 2008; Gambs, 2008; Horn and Gottlieb, 2001; Nasios and Bors, 2007), a field which studies theories and constructions of systems that can learn from data, among which classification is a typical task.
Page 1, “Introduction”
- build a computational model based on quantum computation theory to handle classification tasks in order to prove the feasibility of applying the QM model to machine learning .
Page 1, “Introduction”
- Our work, however, focuses on developing a novel method which explores the relationship between machine learning model with physical world, in order to investigate these models by physical rule which describe our universe.
Page 4, “Discussion”
- We hope our attempt will shed some light upon the application of quantum theory into the field of machine learning .
Page 4, “Discussion”
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text classification
Appears in 3 sentences as: text classification (3)
In A Novel Classifier Based on Quantum Computation
- Specifically, in our experiment, we assigned the term frequency, a feature frequently used in text classification to rn , and treated the phase 0" as a constant, since we found the phase makes little contribution to the classification.
Page 2, “Basic principle of quantum classifier”
- We present here our model of text classification and compare it with SVM and KNN on two datasets.
Page 4, “Discussion”
- Moreover, the QC performs well in text classification compared with SVM and KNN and outperforms them on small-scale training sets.
Page 4, “Discussion”
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