scholarly journals Combining and Comparing Multiple Algorithms for Better Learning and Classification: A Case Study of MARF

10.5772/10248 ◽  
2010 ◽  
Author(s):  
Serguei Mokhov
Keyword(s):  
Multiple Algorithms

A Comparative Study of Clustering Algorithms

2011 ◽  
Vol 3 (3) ◽  
pp. 1-18
Author(s):  
Kanna AlFalahi ◽  
Saad Harous ◽  
Yacine Atif
Keyword(s):  
Social Networks ◽  
Comparative Study ◽  
Collaborative Filtering ◽  
Community Detection ◽  
Clustering Algorithms ◽  
Social Web ◽  
Web Data ◽  
Huge Data ◽  
Multiple Algorithms

Clustering is a major problem when dealing with organizing and dividing data. There are multiple algorithms proposed to handle this issue in many scientific areas such as classifications, community detection and collaborative filtering. The need for clustering arises in Social Networks where huge data generated daily and different relations are established between users. The ability to find groups of interest in a network can help in many aspects to provide different services such as targeted advertisements. The authors surveyed different clustering algorithms from three different clustering groups: Hierarchical, Partitional, and Density-based algorithms. They then discuss and compare these algorithms from social web point view and show their strength and weaknesses in handling social web data. They also use a case study to support our finding by applying two clustering algorithms on articles collected from Delicious.com and discussing the different groups generated by each algorithm.

scholarly journals Sample size calculations for the experimental comparison of multiple algorithms on multiple problem instances

2020 ◽  
Vol 26 (6) ◽  
pp. 851-883
Author(s):  
Felipe Campelo ◽  
Elizabeth F. Wanner
Keyword(s):  
Sample Size ◽  
Statistical Power ◽  
Experimental Comparison ◽  
Scheduling Problems ◽  
Significance Level ◽  
Problem Class ◽  
Sample Size Calculations ◽  
Problem Instances ◽  
Multiple Algorithms

Abstract This work presents a statistically principled method for estimating the required number of instances in the experimental comparison of multiple algorithms on a given problem class of interest. This approach generalises earlier results by allowing researchers to design experiments based on the desired best, worst, mean or median-case statistical power to detect differences between algorithms larger than a certain threshold. Holm’s step-down procedure is used to maintain the overall significance level controlled at desired levels, without resulting in overly conservative experiments. This paper also presents an approach for sampling each algorithm on each instance, based on optimal sample size ratios that minimise the total required number of runs subject to a desired accuracy in the estimation of paired differences. A case study investigating the effect of 21 variants of a custom-tailored Simulated Annealing for a class of scheduling problems is used to illustrate the application of the proposed methods for sample size calculations in the experimental comparison of algorithms.

A Comparative Study of Clustering Algorithms

2013 ◽  
pp. 121-137
Author(s):  
Kanna Al Falahi ◽  
Saad Harous ◽  
Yacine Atif
Keyword(s):  
Social Networks ◽  
Comparative Study ◽  
Collaborative Filtering ◽  
Community Detection ◽  
Clustering Algorithms ◽  
Social Web ◽  
Web Data ◽  
Huge Data ◽  
Multiple Algorithms

Clustering is a major problem when dealing with organizing and dividing data. There are multiple algorithms proposed to handle this issue in many scientific areas such as classifications, community detection and collaborative filtering. The need for clustering arises in Social Networks where huge data generated daily and different relations are established between users. The ability to find groups of interest in a network can help in many aspects to provide different services such as targeted advertisements. The authors surveyed different clustering algorithms from three different clustering groups: Hierarchical, Partitional, and Density-based algorithms. They then discuss and compare these algorithms from social web point view and show their strength and weaknesses in handling social web data. They also use a case study to support our finding by applying two clustering algorithms on articles collected from Delicious.com and discussing the different groups generated by each algorithm.

The Genesis and Internal Dynamics of El Salvador's People's Revolutionary Army, 1970–1976

2014 ◽  
Vol 38 (01) ◽  
pp. 102-129
Author(s):  
ALBERTO MARTÍN ÁLVAREZ ◽  
EUDALD CORTINA ORERO
Keyword(s):  
Latin America ◽  
El Salvador ◽  
Early Years ◽  
Left Wing ◽  
Internal Dynamics ◽  
Internal Coherence ◽  
The 1960S

AbstractUsing interviews with former militants and previously unpublished documents, this article traces the genesis and internal dynamics of the Ejército Revolucionario del Pueblo (People's Revolutionary Army, ERP) in El Salvador during the early years of its existence (1970–6). This period was marked by the inability of the ERP to maintain internal coherence or any consensus on revolutionary strategy, which led to a series of splits and internal fights over control of the organisation. The evidence marshalled in this case study sheds new light on the origins of the armed Salvadorean Left and thus contributes to a wider understanding of the processes of formation and internal dynamics of armed left-wing groups that emerged from the 1960s onwards in Latin America.

Culture and the plasticity of perception

2020 ◽  
Vol 43 ◽  
Author(s):  
Michael Lifshitz ◽  
T. M. Luhrmann
Keyword(s):  
Cultural Context ◽  
Sensory Experience ◽  
Cultural Learning ◽  
The World

Abstract Culture shapes our basic sensory experience of the world. This is particularly striking in the study of religion and psychosis, where we and others have shown that cultural context determines both the structure and content of hallucination-like events. The cultural shaping of hallucinations may provide a rich case-study for linking cultural learning with emerging prediction-based models of perception.

Dual systems for all: Higher-order, role-based relational reasoning as a uniquely derived feature of human cognition

2019 ◽  
Vol 42 ◽  
Author(s):  
Daniel J. Povinelli ◽  
Gabrielle C. Glorioso ◽  
Shannon L. Kuznar ◽  
Mateja Pavlic
Keyword(s):  
Temporal Reasoning ◽  
Higher Order ◽  
Important Case ◽  
Human Cognition ◽  
Relational Reasoning ◽  
Dual Systems ◽  
First Order ◽  
Reasoning System ◽  
Role Based

Abstract Hoerl and McCormack demonstrate that although animals possess a sophisticated temporal updating system, there is no evidence that they also possess a temporal reasoning system. This important case study is directly related to the broader claim that although animals are manifestly capable of first-order (perceptually-based) relational reasoning, they lack the capacity for higher-order, role-based relational reasoning. We argue this distinction applies to all domains of cognition.

Sociocultural memory development research drives new directions in gadgetry science

2019 ◽  
Vol 42 ◽  
Author(s):  
Penny Van Bergen ◽  
John Sutton
Keyword(s):  
Episodic Memory ◽  
Autobiographical Memory ◽  
Developmental Psychology ◽  
Cross Cultural ◽  
Memory Development ◽  
Development Research ◽  
Cultural Research ◽  
New Directions ◽  
Cross Cultural Research

Abstract Sociocultural developmental psychology can drive new directions in gadgetry science. We use autobiographical memory, a compound capacity incorporating episodic memory, as a case study. Autobiographical memory emerges late in development, supported by interactions with parents. Intervention research highlights the causal influence of these interactions, whereas cross-cultural research demonstrates culturally determined diversity. Different patterns of inheritance are discussed.

Construction of plastic contact deformation maps on ceramics: a case study on aluminum nitride

1996 ◽  
Vol 54 ◽  
pp. 636-637
Author(s):  
D. L. Callahan
Keyword(s):  
Plastic Deformation ◽  
Aluminum Nitride ◽  
Mechanical Response ◽  
Three Dimensional ◽  
Bright Field Image ◽  
Perfectly Plastic ◽  
Contrast Analysis ◽  
Deformation Patterns

Modern polishing, precision machining and microindentation techniques allow the processing and mechanical characterization of ceramics at nanometric scales and within entirely plastic deformation regimes. The mechanical response of most ceramics to such highly constrained contact is not predictable from macroscopic properties and the microstructural deformation patterns have proven difficult to characterize by the application of any individual technique. In this study, TEM techniques of contrast analysis and CBED are combined with stereographic analysis to construct a three-dimensional microstructure deformation map of the surface of a perfectly plastic microindentation on macroscopically brittle aluminum nitride.The bright field image in Figure 1 shows a lg Vickers microindentation contained within a single AlN grain far from any boundaries. High densities of dislocations are evident, particularly near facet edges but are not individually resolvable. The prominent bend contours also indicate the severity of plastic deformation. Figure 2 is a selected area diffraction pattern covering the entire indentation area.

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