本文選題：粗糙集 + 馬田系統(tǒng)�。� 參考：《南京理工大學(xué)》2015年碩士論文

【摘要】：外資銀行憑借先進(jìn)的營(yíng)銷策略對(duì)我國(guó)的商業(yè)銀行產(chǎn)生了巨大沖擊,國(guó)內(nèi)客戶對(duì)產(chǎn)品和服務(wù)的需求趨于多樣化和個(gè)性化,眾多依靠傳統(tǒng)模式開拓市場(chǎng)的國(guó)內(nèi)商業(yè)銀行無(wú)法保持良好的市場(chǎng)競(jìng)爭(zhēng)力,國(guó)內(nèi)商業(yè)銀行亟需改變傳統(tǒng)營(yíng)銷策略。直接營(yíng)銷作為一種以客戶需求為中心的新型營(yíng)銷模式已在國(guó)外得到廣泛應(yīng)用,國(guó)內(nèi)銀行采用直接營(yíng)銷模式將有助于提升市場(chǎng)競(jìng)爭(zhēng)力,而直接營(yíng)銷模式得以有效實(shí)施的關(guān)鍵在于找到合適的方法通過(guò)客戶分類定位目標(biāo)客戶。常用分類方法通常需要對(duì)數(shù)據(jù)分布進(jìn)行假設(shè),而馬田系統(tǒng)作為一種新的模式識(shí)別方法是基于數(shù)據(jù)進(jìn)行分析完成分類的,而且它能刪除冗余變量,提取有效信息,真正實(shí)現(xiàn)系統(tǒng)降維,馬田系統(tǒng)已成功應(yīng)用于多個(gè)行業(yè)的分類問題中。本文針對(duì)馬田系統(tǒng)在篩選特征變量方面的不足引入粗糙集理論,構(gòu)建基于粗糙集的改進(jìn)馬田系統(tǒng)方法,并將改進(jìn)的馬田系統(tǒng)應(yīng)用于銀行直接營(yíng)銷客戶分類問題中,定位目標(biāo)客戶。本文的主要研究?jī)?nèi)容包括以下兩個(gè)方面：(1)基于粗糙集的馬田系統(tǒng)理論研究傳統(tǒng)馬田系統(tǒng)結(jié)合正交表和信噪比篩選有效特征變量以優(yōu)化基準(zhǔn)空間,但有學(xué)者研究表明,正交表與信噪比方法在篩選有效特征變量方面存在不足。本文引入粗糙集理論替代正交表和信噪比對(duì)特征變量進(jìn)行選擇,構(gòu)建基于粗糙集的馬田系統(tǒng)分類方法,以更好地優(yōu)化基準(zhǔn)空間、改善分類效果。(2)基于粗糙集的馬田系統(tǒng)應(yīng)用研究為研究國(guó)內(nèi)銀行開展直接營(yíng)銷的客戶分類問題,選取UCI數(shù)據(jù)集中某葡萄牙銀行直接營(yíng)銷活動(dòng)相關(guān)數(shù)據(jù)作為分析數(shù)據(jù),進(jìn)行基于粗糙集的馬田系統(tǒng)應(yīng)用研究。分別用基于粗糙集的馬田系統(tǒng)和傳統(tǒng)馬田系統(tǒng)分析銀行客戶數(shù)據(jù)進(jìn)行客戶分類,并對(duì)比二者篩選的有效特征變量個(gè)數(shù)及分類準(zhǔn)確率。結(jié)論表明：與傳統(tǒng)馬田系統(tǒng)相比,基于粗糙集的馬田系統(tǒng)不僅提升了分類準(zhǔn)確率,而且減少了有效特征變量個(gè)數(shù),可以進(jìn)行準(zhǔn)確分類并簡(jiǎn)化信息收集工作。基于粗糙集的馬田系統(tǒng)方法可以應(yīng)用于銀行直接營(yíng)銷客戶問題中進(jìn)行準(zhǔn)確的客戶定位,有助于國(guó)內(nèi)銀行有效實(shí)施直接營(yíng)銷模式。與此同時(shí),基于粗糙集的馬田系統(tǒng)方法可以應(yīng)用于其他分類問題中。
[Abstract]:With the advanced marketing strategy, the foreign banks have a great impact on our commercial banks. The domestic customers' demand for products and services tends to diversify and individualize. Many domestic commercial banks relying on the traditional mode can not maintain a good market competitiveness. The commercial banks in the country need to change the traditional marketing strategy. As a new marketing mode centered on customer demand, marketing is widely used abroad. The direct marketing mode of domestic banks will help to improve the market competitiveness. The key to the effective implementation of the direct marketing model is to find the right way to locate the target customers through customer classification. The data distribution is usually supposed to be assumed, and the Martin system is a new pattern recognition method based on data analysis, and it can delete redundant variables, extract effective information, and truly realize the system reduction. The Martin system has been successfully applied to the classification of many industries. This paper is aimed at Martin system in this paper. The shortage of feature variables is introduced into the rough set theory, and the improved Martin system method based on rough sets is constructed, and the improved Martin system is applied to the customer classification problem of direct marketing of banks. The main research contents of this paper include the following two aspects: (1) the research of Martin system theory based on Rough Set Traditional Martin system combines orthogonal tables and signal-to-noise ratio to filter effective feature variables to optimize the reference space, but some scholars have shown that there is a shortage of orthogonal tables and signal-to-noise ratio methods in screening effective feature variables. The field system classification method is used to better optimize the reference space and improve the classification effect. (2) the application of Martin system based on rough sets is used to study the customer classification problem of direct marketing in domestic banks. The data of the direct marketing activities of a Portuguese bank in a UCI data set are selected as the analysis data, and the Martin system based on rough sets is carried out. Use the Martin system based on rough set and the traditional Martin system to analyze the customer data of the bank, and compare the number of effective feature variables and the classification accuracy of the two parties. The conclusion shows that compared with the traditional Martin system, the Martin system based on rough set not only improves the classification accuracy, but also reduces the classification accuracy. Without the number of effective feature variables, we can classify and simplify the information collection. The Martin system method based on rough sets can be applied to the accurate customer location in the bank direct marketing customer problems and help the domestic banks to implement the direct marketing model effectively. At the same time, the rough set based Martin system method can be used. It is applied to other classification problems.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：F832.33

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相關(guān)期刊論文 前1條

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本文編號(hào)：2117828