Results 251 to 260 of about 4,817,340 (289)

Performance Analysis Of Fuzzy Rough Set-Based And Correlation-Based Attribute Selection Methods On Detection Of Chronic Kidney Disease With Various Classifiers

2019 Scientific Meeting on Electrical-Electronics & Biomedical Engineering and Computer Science (EBBT), 2019
Technological developments generally have positive effects on our daily lives especially on health domain. Diagnosing diseases through new machines or methods are easier than compared to the past. Benchmarking the effect of attribute selection methods on
Muhammet Sinan Başarslan, F. Kayaalp
semanticscholar   +1 more source

Cacao quality: Highlighting selected attributes

Food Reviews International, 2016
ABSTRACTWorld demand for cacao and the requirements for quality beans have increased every year. Research studies have developed standards for aspects of cacao quality that meet industrial criteria as well as international import and export legislation that is aimed at food security.
Guilherme A. H. A. Loureiro, Quintino R. Araujo, George A. Sodré, Raúl R. Valle, José O. Souza, Edson M. L. S. Ramos, Nicholas B. Comerford, Pauline F. Grierson   +7 more
openaire   +1 more source

A Structured Approach to Attribute Selection in Economic Valuation Studies: Using Q-methodology

, 2019
The literature on economic valuation of ecosystem services increasingly recognizes that the welfare generating endpoint of biophysical changes could potentially be heterogeneous across individuals in the population. This paper suggests Q-methodology as a
Anne Kejser Jensen
semanticscholar   +1 more source

A Novel Attribute Selection Mechanism for Video Captioning

International Conference on Information Photonics, 2019
Attributes are more and more popular for enhancing the performance of video captioning which requires semantic understanding of videos and the ability of generating natural language descriptions.
Huanhou Xiao, Jinglun Shi
semanticscholar   +1 more source

Stochastic Attribute Selection Committees

1998
Classifier committee learning methods generate multiple classifiers to form a committee by repeated application of a single base learning algorithm. The committee members vote to decide the final classification. Two such methods, Bagging and Boosting, have shown great success with decision tree learning.
Zijian Zheng, Geoffrey I. Webb
openaire   +1 more source

Attribute selection in seismic facies classification: Application to a Gulf of Mexico 3D seismic survey and the Barnett Shale

Interpretation, 2019
Automated seismic facies classification using machine-learning algorithms is becoming more common in the geophysics industry. Seismic attributes are frequently used as input because they may express geologic patterns or depositional environments better ...
Yuji Kim, Robert G. Hardisty, K. Marfurt
semanticscholar   +1 more source

Attributed intentions and informational selectivity

Journal of Experimental Social Psychology, 1974
Abstract Three experiments tested the hypothesis that ascribing a specific intention to an actor prior to witnessing his behavior leads an observer to preferentially recall action bearing on the intention. In each case, subjects were exposed to an action sequence which mixed elements appropriate to more than one intention.
Jerry Zadny, Harold B Gerard
openaire   +1 more source

Attribute cut-offs in freight service selection

Transportation Research Part E: Logistics and Transportation Review, 2007
The paper applies the choice model incorporating attribute cut-offs proposed by [Swait, J.D., 2001. A non-compensatory choice model incorporating attribute cutoffs. Transportation Research: Part B 35 (10), 903–928] to evaluate shippers’ preferences for freight service attributes. A stated preference experiment on a sample of Italian manufacturing firms
DANIELIS, ROMEO, MARCUCCI
openaire   +2 more sources

Attributes: Selective Learning and Influence

Econometrica
An agent selectively samples attributes of a complex project so as to influence the decision of a principal. The players disagree about the weighting, or relevance, of attributes. The correlation across attributes is modeled through a Gaussian process, the covariance function of which captures pairwise attribute similarity.
openaire   +2 more sources

On Soft Partition Attribute Selection

2012
Rough set theory provides a methodology for data analysis based on the approximation of information systems. It is revolves around the notion of discernibility i.e. the ability to distinguish between objects based on their attributes value. It allows inferring data dependencies that are useful in the fields of feature selection and decision model ...
Rabiei Mamat, Tutut Herawan, Noraziah Ahmad, Mustafa Mat Deris   +3 more
openaire   +1 more source