Search Results - subject:"symbolic data analysis"

SymScal: symbolic multidimensional scaling of interval dissimilarities

Groenen, Patrick; Winsberg, S.; Rodriguez, O.; Diday, E. - Faculteit der Economische Wetenschappen, Erasmus … - 2005

Multidimensional scaling aims at reconstructing dissimilarities between pairs of objects by distances in a low dimensional space. However, in some cases the dissimilarity itself is unknown, but the range of the dissimilarity is given. Such fuzzy data fall in the wider class of symbolic data...

Persistent link: https://www.econbiz.de/10010837961

SymScal: symbolic multidimensional scaling of interval dissimilarities

Groenen, P.J.F.; Winsberg, S.; Rodriguez, O.; Diday, E. - Erasmus University Rotterdam, Econometric Institute - 2005

- valued data. An inherent part of symbolic data analysis is the definition of a symbolic object. A symbolic object is a model … discuss the use of SymScal on empirical dissimilarity intervals of sounds. Keywords: Multidimensional scaling, Symbolic data … analysis, Iterative ma- jorization, Distance smoothing, SymScal. ⁄Econometric Institute, Erasmus University Rotterdam, P.O. Box …

Persistent link: https://www.econbiz.de/10005000465

Standardization of interval symbolic data based on the empirical descriptive statistics

Guo, Junpeng; Li, Wenhua; Li, Chenhua; Gao, Sa - In: Computational Statistics & Data Analysis 56 (2012) 3, pp. 602-610

interval data obtained by symbolic data analysis (SDA). SDA is a new data analysis technique which captures the value of a …

Persistent link: https://www.econbiz.de/10010574475

Principal component analysis with interval imputed missing values

Zuccolotto, Paola - In: AStA Advances in Statistical Analysis 96 (2012) 1, pp. 1-23

Persistent link: https://www.econbiz.de/10010539408

Holt’s exponential smoothing and neural network models for forecasting interval-valued time series

Maia, André Luis Santiago; Carvalho, Francisco de A.T. de - In: International Journal of Forecasting 27 (2011) 3, pp. 740-759

Interval-valued time series are interval-valued data that are collected in a chronological sequence over time. This paper introduces three approaches to forecasting interval-valued time series. The first two approaches are based on multilayer perceptron (MLP) neural networks and Holt’s...

Persistent link: https://www.econbiz.de/10010577319

Clustering constrained symbolic data

De A. T. De Carvalho, Francisco; Csernel, Marc; … - Université Paris-Dauphine (Paris IX) - 2009

Dealing with multi-valued data has become quite common in both the framework of databases as well as data analysis. Such data can be constrained by domain knowledge provided by relations between the variables and these relations are expressed by rules. However, such knowledge can introduce a...

Persistent link: https://www.econbiz.de/10010733994

Linear discriminant analysis for interval data

Silva, António; Brito, Paula - In: Computational Statistics 21 (2006) 2, pp. 289-308

Persistent link: https://www.econbiz.de/10005613175

Dynamic clustering for interval data based on L <Subscript>2</Subscript> distance

Carvalho, Francisco; Brito, Paula; Bock, Hans-Hermann - In: Computational Statistics 21 (2006) 2, pp. 231-250

Persistent link: https://www.econbiz.de/10005166782

Extension of multivariate regression trees to interval data. Application to electricity load profiling

Cariou, Véronique - In: Computational Statistics 21 (2006) 2, pp. 325-341

Persistent link: https://www.econbiz.de/10005184310