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MICAI
2007
Springer
13 years 11 months ago
Weighted Instance-Based Learning Using Representative Intervals
Instance-based learning algorithms are widely used due to their capacity to approximate complex target functions; however, the performance of this kind of algorithms degrades signi...
Octavio Gómez, Eduardo F. Morales, Jes&uacu...
CIARP
2007
Springer
13 years 11 months ago
Image Segmentation Using Automatic Seeded Region Growing and Instance-Based Learning
Segmentation through seeded region growing is widely used because it is fast, robust and free of tuning parameters. However, the seeded region growing algorithm requires an automat...
Octavio Gómez, Jesús A. Gonzá...
WISE
2005
Springer
13 years 10 months ago
Extracting Web Data Using Instance-Based Learning
This paper studies structured data extraction from Web pages, e.g., online product description pages. Existing approaches to data extraction include wrapper induction and automatic...
Yanhong Zhai, Bing Liu
ANSS
1998
IEEE
13 years 9 months ago
On Interval Weighted Three-Layer Neural Networks
In solving application problems, the data sets used to train a neural network may not be hundred percent precise but within certain ranges. Representing data sets with intervals, ...
Mohsen Beheshti, Ali Berrached, André de Ko...
JSAI
2001
Springer
13 years 9 months ago
Optimistic Priority Weights with an Interval Comparison Matrix
: AHP is proposed to give the importance grade with respect to many items. The comparison value that is the element of a comparison matirx is used to be crisp, however, it is easy ...
Tomoe Entani, Hidetomo Ichihashi, Hideo Tanaka