Results 261 to 270 of about 846,763 (295)
Some of the next articles are maybe not open access.
2009
It is well known fact that proteins are grouped in families according to their structure, function and ancestry. Proteins that evolve from a common ancestor can have modified functionalities. So, we divide protein families into subfamilies according to the modified functionality.
Špoljarić, Drago +4 more
openaire
It is well known fact that proteins are grouped in families according to their structure, function and ancestry. Proteins that evolve from a common ancestor can have modified functionalities. So, we divide protein families into subfamilies according to the modified functionality.
Špoljarić, Drago +4 more
openaire
Question selection for multi-attribute decision-aiding
European Journal of Operational Research, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Holloway, Hillary A. +1 more
openaire +2 more sources
Feature selections for authorship attribution
Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013The authorship attribution (AA) problem can be viewed as a categorization problem. To determine the most effective features to discriminate between different authors, we have evaluated six independent feature-scoring selection functions (information gain, pointwise mutual information, odds ratio, χ2, DIA, and the document frequency (df)).
openaire +1 more source
Attribute selection on student performance dataset using maximum dependency attribute
2017 5th International Conference on Electrical, Electronics and Information Engineering (ICEEIE), 2017As a higher education institution, knowing which GPA of the semester has the most determinant to affecting the academic performance of students is important yet challenging. Therefore, this paper deliberates the usage of rough set theory based Maximum Dependency Attributes (MDA). The dataset is taken from the Directorate of Information Systems (SISFO),
Rd Rohmat Saedudin +4 more
openaire +1 more source
Attribute and object selection queries on objects with probabilistic attributes
ACM Transactions on Database Systems, 2012Modern data processing techniques such as entity resolution, data cleaning, information extraction, and automated tagging often produce results consisting of objects whose attributes may contain uncertainty. This uncertainty is frequently captured in the form of a set of multiple mutually exclusive value choices for each uncertain ...
Rabia Nuray-Turan +3 more
openaire +1 more source
Quantum-inspired attribute selection algorithms
Quantum Science and TechnologyAbstract In this study, we propose the use of quantum information gain (QIG) and fidelity as quantum splitting criteria to construct an efficient and balanced quantum decision tree. QIG is a circuit-based criterion in which angle embedding is used to construct a quantum state, which utilizes quantum mutual information to compute the ...
Diksha Sharma +2 more
openaire +1 more source
2012 International Conference on Radar, Communication and Computing (ICRCC), 2012
Data mining is a process of finding hidden information from databases storing historical data which are also known as data-warehouses. Classification being a very well-known data mining technique, groups similar data objects by establishing relationship between the objects under test and the pre-defined class labels obtained during training phase.
openaire +1 more source
Data mining is a process of finding hidden information from databases storing historical data which are also known as data-warehouses. Classification being a very well-known data mining technique, groups similar data objects by establishing relationship between the objects under test and the pre-defined class labels obtained during training phase.
openaire +1 more source
The Selection of the Attributes
1971The problem of how to select an effective set of attributes for a PRD is generally considered the single most difficult problem in the design. The problem is frequently discussed in the literature (Levine 1969; Nagy 1969; Nelson and Levy; Fu et al. 1970; Henderson and Lainiotis 1970) and is the topic of September 1971 issue of the IEEE Transactions on ...
openaire +1 more source
Attribute Selection Based on Reduction of Numerical Attributes During Discretization
2017Some numerical attributes may be reduced during discretization. It happens when a discretized attribute has only one interval, i.e., the entire domain of a numerical attribute is mapped into a single interval. The problem is how such reduction of data sets affects the error rate measured by the C4.5 decision tree generation system using ten-fold cross ...
Jerzy W. Grzymała-Busse, Teresa Mroczek
openaire +1 more source
A data-level fusion model for unsupervised attribute selection in multi-source homogeneous data
Information Fusion, 2022Pengfei Zhang, Zhong Yuan, Chuan Luo
exaly