利用遗传规划分类器进行弥漫性大b细胞淋巴瘤分类

S. Hengpraprohm, P. Chongstitvatana
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引用次数: 7

摘要

弥漫性大b细胞淋巴瘤(DLBCL)是最常见的非霍奇金淋巴瘤亚型。利用监测基因表达的cDNA微阵列技术的数据,可以对正常和DLBCL患者进行分类。机器学习技术是众所周知的分类任务方法。本文提出了一种基于遗传规划的分类器生成方法。该方法采用分类器聚类对结果进行投票。此外,分类器以数学方程的形式呈现,可修改为人类解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diffuse Large B-cell Lymphoma Classification Using Genetic Programming Classifier
Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin’s lymphoma. It is possible to classify normal and DLBCL patients using the data from cDNA microarrays technique that monitoring gene expression. Machine learning techniques are well-known methods for classification tasks. In this paper, we propose a Genetic Programming based method to generate classifiers with high accuracy. The proposed method employs cluster of classifiers to vote for the result. Furthermore, the classifier is presented in form of a mathematical equation which is amendable to human interpretation.
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