Spaces of closest fit

Closest Spectral Fit for Removing Clouds and Cloud Shadows

Completely cloud-free remotely sensed images are preferred, but they are not always available. Although the average cloud coverage for the entire planet is about 40 percent, the removal of clouds and cloud shadows is rarely studied. To address this problem, a closest spectral fit method is developed to replace cloud and cloud-shadow pixels with their most similar nonclouded pixel values. The ob...

some properties of fuzzy hilbert spaces and norm of operators

in this thesis, at first we investigate the bounded inverse theorem on fuzzy normed linear spaces and study the set of all compact operators on these spaces. then we introduce the notions of fuzzy boundedness and investigate a new norm operators and the relationship between continuity and boundedness. and, we show that the space of all fuzzy bounded operators is complete. finally, we define...

A Closest Fit Approach to Missing Attribute VAlues in Preterm Birth Data

Recently, results on a comparison of seven successful methods of handling missing attribute values were reported. This paper describes experimental results on the three most successful methods out of these seven. Two of these methods, based on a Closet Fit idea (searching in a remaining data set for the closest fit case and replacing a missing attribute value by the corresponding known value fr...

Roleo: Visualising Thematic Fit Spaces on the Web

In this paper, we present Roleo, a web tool for visualizing the vector spaces generated by the evaluation of distributional memory (DM) models over thematic fit judgements. A thematic fit judgement is a rating of the selectional preference of a verb for an argument that fills a given thematic role. The DM approach to thematic fit judgements involves the construction of a sub-space in which a pr...

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