An Improvement of Method Handling Missing Values in Incomplete Information System

نویسندگان

  • Hung Quoc Nguyen
  • Duc Thuan Nguyen
چکیده

Many methods have been proposed to process missing data for information system. In the paper, we modified an algorithm to handle missing value based on covering rough sets model previously reported by Dai Dai and Jianpeng Wang proposed to transform an incomplete information system into a complete information system. The experimental results show that the new version of algorithm is efficient. Keywords— Rough sets, Covering rough sets, Incomplete Information system

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Investigating the missing data effect on credit scoring rule based models: The case of an Iranian bank

Credit risk management is a process in which banks estimate probability of default (PD) for each loan applicant. Data sets of previous loan applicants are built by gathering their data, and these internal data sets are usually completed using external credit bureau’s data and finally used for estimating PD in banks. There is also a continuous interest for bank to use rule based classifiers to b...

متن کامل

A BAYESIAN APPROACH TO COMPUTING MISSING REGRESSOR VALUES

In this article, Lindley's measure of average information is used to measure the information contained in incomplete observations on the vector of unknown regression coefficients [9]. This measure of information may be used to compute the missing regressor values.

متن کامل

Solving Incomplete Datasets in Soft Set Using Supported Sets and Aggregate Values

The theory of soft set proposed by Molodtsovin 1999[1]is a new method for handling uncertain data and can be defined as a Boolean-valued information system. Ithas been applied to data analysis and decision support systems based on large datasets. In this paper, it is shown that calculated support value can be used to determine missing attribute value of an object. However, in cases when more th...

متن کامل

تحلیل درستنمایی ماکزیمم مدل رگرسیون لجستیک در حالتی که داده های متغیرهای پیشگو کامل نیستند ولی متغیرهای کمکی وجود دارند

Background and Objectives: Missing data exist in many studies, e.g. in regression models, and they decrease the model's efficacy. Many methods have been suggested for handling incomplete data: they have generally focused on missing outcome values. But covariate values can also be missing.Materials and Methods: In this paper we study the missing imputation by the EM algorithm and auxiliary varia...

متن کامل

An Incomplete Data Filling Approach Based on a New Valued Tolerance Relation

Abstract: In real life there are many incomplete information system, However, the traditional rough set theory is not suitable for incomplete information system. A lot of extension of the rough sets theory have been proposed based on this. In these theories, the handling of null value or missing values is the key problem. In this paper a new valued tolerance and a concept of Tolerance Degree Ve...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013