دانلود مقاله ISI انگلیسی شماره 22083
عنوان فارسی مقاله

استدلال روش جدید داده کاوی ترکیبی با استفاده از یک مورد مبتنی بر رگرسیون : کاربرد برای پیش بینی مالی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
22083 2006 8 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
A new hybrid data mining technique using a regression case based reasoning: Application to financial forecasting
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 31, Issue 2, August 2006, Pages 329–336

کلمات کلیدی
استدلال موردی مبتنی بر رگرسیون - هوش مصنوعی - داده کاوی - استدلال موردی - شبکه های عصبی - روش های آماری - روش های یادگیری
پیش نمایش مقاله
پیش نمایش مقاله استدلال روش جدید داده کاوی ترکیبی با استفاده از یک مورد مبتنی بر رگرسیون : کاربرد برای پیش بینی مالی

چکیده انگلیسی

This paper proposes a regression case based reasoning (RCBR) which applies different weights to independent variables before finding similar cases. The traditional CBR model has focused on finding similar cases from a case base without considering the importance of independent variables. Thus, when extracting similar cases the traditional CBR has put same weights on each independent variable. The proposed regression CBR (RCBR) finds a relative importance of independent variables from the relationship between independent variables and a dependent variable using a regression analysis and puts relative weights using regression coefficients on independent variables. Then, it selects nearest neighbor or similar cases using weighted independent variables through the traditional CBR machine and updates weights dynamically for the next target case and again performs the traditional CBR machine.

مقدمه انگلیسی

This paper proposes a new hybrid learning technique, a regression CBR (RCBR) which applies different weights to independent variables before finding similar cases. The traditional CBR model has focused on finding similar cases from a case base without considering the importance of independent variables. Thus, when extracting similar cases the traditional CBR has put same weights on each independent variable. The proposed regression CBR (RCBR) finds a relative importance of independent variables from the relationship between independent variables and a dependent variable using a regression analysis and applies relative weights using regression coefficients to independent variables. Then, it selects nearest neighbor or similar cases using weighted independent variables through the traditional CBR machine and updates weights dynamically for the next target case and again performs the traditional CBR machine. These concepts are investigated against the backdrop of a practical application involving the prediction of a stock market index. The rest of this paper is organized into five sections. Section 2 reviews case based reasoning (CBR) as a knowledge discovery technique. Section 3 introduces a regression CBR. Section 4 presents the case study and reports the results. The case study intends to investigate the effect of a regression CBR on the predictive performance in forecasting a stock market index. Finally, the concluding remarks are presented in Section 6.

نتیجه گیری انگلیسی

In recent years, data mining techniques such as neural networks, CBR have been applied extensively to the task of predicting financial variables. This paper proposed a new case based reasoning technique which concepts are investigated against the backdrop of a practical application involving the prediction of a stock market index. The regression CBR was significantly better than random walk and was better than standard CBR models in the hit rate measure as well as was seen to surpass other models in the MAPE. In fact, the literature contains numerous varieties of learning techniques such as neural networks, induction and genetic algorithms. Thus, the systematic evaluation of a larger collection of learning techniques represents a rich area for future investigation. Also a promising direction for the future is a trading strategy through integrating a regression CBR and other learning techniques for financial market.

خرید مقاله
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