Abstract: Sensitivity analysis is a powerful method for discovering the significant factors that contribute to understanding the interaction between variables in multivariate datasets. A number of sensitivity analysis methods fall into the class of local analysis, in which the sensitivity is defined as the partial derivatives of a target variable with respect to a group of independent variables. In a recent paper, we presented a novel pointwise local pattern exploration system for visual sensitivity analysis. Using this system, analysts are able to explore local patterns and the sensitivity at individual data points, which reveals the relationships between a focal point and its neighbors. In this paper we present several evaluations of the ...
We often need to report on environmental, economic and social indicators, and properties at aggregat...
A key hypothesis in sensory system neuroscience is that sensory representations are adapted to the s...
The visual environment for observers is usually complex, and it is impossible for the human visual s...
The performance of a visual system is strongly influenced by the information processing that is done...
Visual Sensitivity analysis has proven its feasibility in data exploration and exposing relationship...
Information visualization can play an important role for exploring model sensitivity to facilitate d...
Figure 1: Boosting of peak points in a pixel-based time series visu-alization. (A) shows two time se...
The solution of several operations research problems requires the creation of a quantitative model. ...
International audienceEngineers and computational scientists often study the behavior of their simul...
In recent years, data analysts have been confronted by increasing amounts of data, often in the form...
Abstract Interactive exploration and analysis of multi-field data utilizes a tight feed-back loop of...
Local forms of spatial analysis focus on exceptions to the general trends represented by more tradit...
There are several supervised learning Data Mining (DM) methods, such as Neural Networks (NN), Suppor...
Data mining for patterns and knowledge discovery in multivariate datasets are very important process...
(A) Sensitivity of the feature values to small changes to the parameter values for the cNAD_ltb mode...
We often need to report on environmental, economic and social indicators, and properties at aggregat...
A key hypothesis in sensory system neuroscience is that sensory representations are adapted to the s...
The visual environment for observers is usually complex, and it is impossible for the human visual s...
The performance of a visual system is strongly influenced by the information processing that is done...
Visual Sensitivity analysis has proven its feasibility in data exploration and exposing relationship...
Information visualization can play an important role for exploring model sensitivity to facilitate d...
Figure 1: Boosting of peak points in a pixel-based time series visu-alization. (A) shows two time se...
The solution of several operations research problems requires the creation of a quantitative model. ...
International audienceEngineers and computational scientists often study the behavior of their simul...
In recent years, data analysts have been confronted by increasing amounts of data, often in the form...
Abstract Interactive exploration and analysis of multi-field data utilizes a tight feed-back loop of...
Local forms of spatial analysis focus on exceptions to the general trends represented by more tradit...
There are several supervised learning Data Mining (DM) methods, such as Neural Networks (NN), Suppor...
Data mining for patterns and knowledge discovery in multivariate datasets are very important process...
(A) Sensitivity of the feature values to small changes to the parameter values for the cNAD_ltb mode...
We often need to report on environmental, economic and social indicators, and properties at aggregat...
A key hypothesis in sensory system neuroscience is that sensory representations are adapted to the s...
The visual environment for observers is usually complex, and it is impossible for the human visual s...