Study on the Extension Models to Handle Missing Values

被引：0

作者：

Yin, Xuri ^{[1
]}

机构：

[1] Inst Automobile Management PLA, Dept Transportat Command, Bengbu 233011, Anhui, Peoples R China

来源：

2010 SECOND ETP/IITA WORLD CONGRESS IN APPLIED COMPUTING, COMPUTER SCIENCE, AND COMPUTER ENGINEERING | 2010年

关键词：

rough set; incomplete information system; tolerance relation; similarity relation; missing values;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The starting point of the rough sets theory is an observation that objects having the same description are indiscernible with respect to the available information. But the indiscernibility relation may be too rigid in some situations. Therefore several generalizations of the rough sets theory have been proposed. Some of them extend the indiscernibility relation using more general similarity or tolerance relations. In this paper, several extension models of rough set under incomplete information are discussed. Furthermore, the performances of these extended relations are compared also.

引用

页码：111 / 114

页数：4

共 50 条

[21] Optimizing regression models for data streams with missing values
Indrė Žliobaitė
Jaakko Hollmén
[J]. Machine Learning, 2015, 99 : 47 - 73
[22] Imputing Missing Values in EEG with Multivariate Autoregressive Models
Kanemura, Atsunori
Cheng, Yuhsen
Kaneko, Takumi
Nozawa, Kento
Fukunaga, Shuichi
[J]. 2018 40TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2018, : 2639 - 2642
[23] An Extension of The Handle Addition Theorem
雷逢春
[J]. Communications in Mathematical Research, 1995, (02) : 144 - 150
[24] Practical guidance to handle missing values in the 25-question Geriatric Locomotive Function Scale (GLFS-25): a simulation study
Kawahara, Takuya
Yamada, Keiko
Terashima, Ryohei
Takashima, Ikumi
Tanaka, Sakae
Ogata, Toru
Chikuda, Hirotaka
Miura, Hiromasa
Nakamura, Kozo
Ohe, Takashi
[J]. BMJ OPEN, 2022, 12 (12): : e065607
[25] Simple methods to handle missing data
Bici, Ruzhdie
[J]. INTERNATIONAL JOURNAL OF COMPUTATIONAL ECONOMICS AND ECONOMETRICS, 2023, 13 (02) : 216 - 242
[26] LEARNING DISEASE PROGRESSION MODELS WITH LONGITUDINAL DATA AND MISSING VALUES
Couronne, Raphael
Vidailhet, Marie
Corvol, Jean Christophe
Lehericy, Stephane
Durrleman, Stanley
[J]. 2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019), 2019, : 1033 - 1037
[27] Missing Values in Multiple Joint Inference of Gaussian Graphical Models
Tozzo, Veronica
Garbarino, Davide
Barla, Annalisa
[J]. INTERNATIONAL CONFERENCE ON PROBABILISTIC GRAPHICAL MODELS, VOL 138, 2020, 138 : 497 - 508
[28] Classification of missing values in spatial data using spin models
Zukovic, Milan
Hristopulos, Dionissios T.
[J]. PHYSICAL REVIEW E, 2009, 80 (01)
[29] Bayesian models for weighted data with missing values: a bootstrap approach
Goldstein, Harvey
Carpenter, James
Kenward, Michael G.
[J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 2018, 67 (04) : 1071 - 1081
[30] Maximum likelihood missing values estimation in patterns of missing MAR and MCAR in structural models.
Costas, CSL
Cabrera, JAH
Santana, GR
[J]. PSICOTHEMA, 1997, 9 (01) : 187 - 197

← 1 2 3 4 5 →