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Seismic attribute selection for machine-learning-based facies analysis
Geophysics, 2020Interpreters face two main challenges in seismic facies analysis. The first challenge is to define, or “label,” the facies of interest. The second challenge is to select a suite of attributes that can differentiate a target facies from the background ...
Jie Qi, Bo Zhang, Bin Lyu, K. Marfurt
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Correlates of Selected Physical Attributes
Research Quarterly. American Association for Health, Physical Education and Recreation, 1969(1969). Correlates of Selected Physical Attributes. Research Quarterly. American Association for Health, Physical Education and Recreation: Vol. 40, No. 3, pp. 637-639.
L J, Dowell, C W, Landiss, E, Mamaliga
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Broad Learning with Attribute Selection for Rheumatoid Arthritis
IEEE International Conference on Systems, Man and Cybernetics, 2020Rheumatoid arthritis (RA) patients have osteoarticular deformation in the early stage, and suffer worse from joint deformity and even loss of function in the later stage.
Jie Yang +7 more
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Attribute selection for modelling
Future Generation Computer Systems, 1997Abstract Modelling a target attribute by other attributes in the data is perhaps the most traditional data mining task. When there are many attributes in the data, one needs to know which of the attribute(s) are relevant for modelling the target, either as a group or the one feature that is most appropriate to select within the model construction ...
Igor Kononenko, Se June Hong
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Coarse-to-Fine Image Aesthetics Assessment With Dynamic Attribute Selection
IEEE transactions on multimediaImage aesthetics assessment (IAA) is an interesting but challenging task, owing to the ineffable nature of human sense of beauty. The study of IAA has evolved from simple binary classification to more complex score regression and distribution prediction.
Yipo Huang +6 more
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Attributional Style, Task Selection and Achievement
Journal of Educational Psychology, 1979The role of causal attributions in determining motivation to achieve has been the object of intensive study with generally interesting and valuable results (Dweck & Goetz, 1978; Weiner, in press). Thus, it seems quite clear that causal attributions play a critical role in determining the perception of success and failure as such (cf.
Leslie J. Fyans, Martin L. Maehr
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1994
Abstract Many real-world domains bless us with a wealth of attributes to use for learning. This blessing is often a curse: most inductive methods generalize worse given too many attributes than if given a good subset of those attributes. We examine this problem for two learning tasks taken from a calendar scheduling domain.
Rich Caruana, Dayne Freitag
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Abstract Many real-world domains bless us with a wealth of attributes to use for learning. This blessing is often a curse: most inductive methods generalize worse given too many attributes than if given a good subset of those attributes. We examine this problem for two learning tasks taken from a calendar scheduling domain.
Rich Caruana, Dayne Freitag
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Lazy attribute selection: Choosing attributes at classification time
Intelligent Data Analysis, 2011Attribute selection is a data preprocessing step which aims at identifying relevant attributes for the target machine learning task – namely classification in this paper. In this paper, we propose a new attribute selection strategy – based on a lazy learning approach – which postpones the identification of relevant attributes until an instance is ...
Pereira, Rafael B. +4 more
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2019 Amity International Conference on Artificial Intelligence (AICAI), 2019
Intrusion Detection Systems (IDS) are administered by analysts for analysing system logs or data packets to predict malware in the network traffic. IDS automate this process for continuously increasing data in the network by using techniques based on ...
A. Chandra, S. Khatri, Rajbala Simon
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Intrusion Detection Systems (IDS) are administered by analysts for analysing system logs or data packets to predict malware in the network traffic. IDS automate this process for continuously increasing data in the network by using techniques based on ...
A. Chandra, S. Khatri, Rajbala Simon
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Attribute Selection for Partially Labeled Categorical Data By Rough Set Approach
IEEE Transactions on Cybernetics, 2017Attribute selection is considered as the most characteristic result in rough set theory to distinguish itself to other theories. However, existing attribute selection approaches can not handle partially labeled data.
Jianhua Dai +4 more
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