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On Difference of Means with Incomplete Data

Biometrika, 1974
SUMMARY An estimate of the difference of means is obtained when sampling from a bivariate normal distribution with variances o-2 and o- and correlation p, where some observations on either of the variables are missing. It is shown that this estimate has desirable properties.
Lin, Pi-Erh, Stivers, Lawrence E.
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Probabilistic Skyline on Incomplete Data

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017
The skyline query is important in database community. In recent years, the researches on incomplete data have been increasingly considered, especially for the skyline query. However, the existing skyline definition on incomplete data cannot provide users with valuable references.
Kaiqi Zhang 0001   +4 more
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On Fuzzy Clustering for Incomplete Spherical Data and for Incomplete Multivariate Categorical Data

2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS), 2018
In this paper, six fuzzy clustering algorithms for incomplete data are proposed that use the optimal completion strategy, three of which are for incomplete spherical data and these of which are for incomplete categorical multivariate data. In numerical experiments using a real dataset, each of the proposed methods outperformed its counterpart method ...
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MISS: Analysis of Incomplete Data

Multivariate Behavioral Research, 1988
MISS is a computer program written in the GAUSS programming language for the microcomputer (with DOS operating system and mathcoprocessor). It provides several options for incomplete data sets. First, it will produce maximum likelihood estimates of the covariance matrix and mean vector via the EM algorithm.
R, Schoenberg, G, Arminger
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A Selective Classifier for Incomplete Data

2008
Classifiers based on feature selection (selective classifiers) are a kind of algorithms that can effectively improve the accuracy and efficiency of classification by deleting irrelevant or redundant attributes of a data set. Due to the complexity of processing incomplete data, however, most of them deal with complete data.
Jingnian Chen   +3 more
openaire   +1 more source

Incomplete data management: a survey

Frontiers of Computer Science, 2017
Incomplete data accompanies our life processes and covers almost all fields of scientific studies, as a result of delivery failure, no power of battery, accidental loss, etc. However, how to model, index, and query incomplete data incurs big challenges.
Xiaoye Miao   +3 more
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ON CLASSIFICATION FOR INCOMPLETE MULTINORMAL DATA

Communications in Statistics - Simulation and Computation, 1973
Using statistics proposed by Hocking and Smith (JASA (1968), 63, 159-173) a multinormal observation vector is classified into one of two normal populations whose mean vectors and covariance matrices are unknown, where the data used for estimation contains both full and partial records.
Smith, W. B., Zeis, C. D.
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On decomposition for incomplete data

Fundam. Informaticae, 2003
Summary: In this paper we present a method of data decomposition to avoid the necessity of reasoning on data with missing attribute values. This method can be applied to any algorithm of classifier induction. The original incomplete data is decomposed into data subsets without missing values.
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Incompleteness in Conceptual Data Modelling

2013
Although conceptual data modelers can ”get creative” when designing entities and relationships to meet business requirements, they are highly constrained by the business rules which determine the details of how the entities and relationships combine. Typically, there is a delay in realising which business rules might be relevant and a further delay in ...
Peter Thanisch   +5 more
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Concept Lattices of Incomplete Data

2012
We present a method of constructing a concept lattice of a formal context with incomplete data. The lattice reduces to a classical concept lattice when the missing values are completed. The lattice also can reflect any known dependencies between the missing values.
Michal Krupka, Jan Lastovicka
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