Search results for "SELECTION"
showing 10 items of 1940 documents
A SELECTION OF METHODS AND TECHNIQUES PROFESSIONAL TEACHERS CAN APPLY TO THEIR OWN LIFELONG LEARNING
2018
A selection of methods and techniques professional teachers can apply to their own lifelong learning.Education is the key to converting knowledge and experience into practical actions, their analysis and application. It plays a key role in the synthesis of new knowledge into research and innovation. Such thoughts on education were expressed in the resolution of the sixth World Education Congress in 2011. Today, when world education forums are widely discussing how schools can better organise the learning process, when ambitious long-term reforms are being implemented in the Latvian education system—the transition to competency-based educational content and teaching methods—it is essential t…
Review Paper: Are reproductive skew models evolutionarily stable?
2003
Reproductive skew theory has become a popular way to phrase problems and test hypotheses of social evolution. The diversity of reproductive skew models probably stems from the ease of generating new variations. However, I show that the logical basis of skew models, that is, the way in which group formation is modelled, makes use of hidden assumptions that may be problematical as they are unlikely to be fulfilled in all social systems. I illustrate these problems by re-analysing the basic concessive skew model with staying incentives. First, the model assumes that dispersal is an all-or-nothing response: all subordinates disperse as soon as concessions drop below a certain value. This leads …
Feature Selection Approach based on Mutual Information and Partial Least Squares
2014
Feature selection technology can improve the modeling accuracy and reduce model’s complexity, especially for the high dimensional spectral data. Aim at this problem, feature selection approach based on mutual information (MI) and partial least square (PLS) is proposed in this paper. MI values between features and responsible variable are calculated, and the threshold value using to select final features is optimal selected based on PLS algorithm. The numbers of the latent values of the PLS and the threshold value of MI are selected according the modeling performance simultaneously. The experimental results based on the near-infrared spectrum show that the proposed approach has better perfor…
Variable selection with unbiased estimation: the CDF penalty
2022
We propose a new SCAD-type penalty in general regression models. The new penalty can be considered a competitor of the LASSO, SCAD or MCP penalties, as it guarantees sparse variable selection, i.e., null regression coefficient estimates, while attenuating bias for the non-null estimates. In this work, the method is discussed, and some comparisons are presented.
Variable Selection with Quasi-Unbiased Estimation: the CDF Penalty
2022
We propose a new non-convex penalty in linear regression models. The new penalty function can be considered a competitor of the LASSO, SCAD or MCP penalties, as it guarantees sparse variable selection while reducing bias for the non-null estimates. We introduce the methodology and present some comparisons among different approaches.
Evaluation of the effect of chance correlations on variable selection using Partial Least Squares -Discriminant Analysis
2013
Variable subset selection is often mandatory in high throughput metabolomics and proteomics. However, depending on the variable to sample ratio there is a significant susceptibility of variable selection towards chance correlations. The evaluation of the predictive capabilities of PLSDA models estimated by cross-validation after feature selection provides overly optimistic results if the selection is performed on the entire set and no external validation set is available. In this work, a simulation of the statistical null hypothesis is proposed to test whether the discrimination capability of a PLSDA model after variable selection estimated by cross-validation is statistically higher than t…
Analyses spectrale et texturale de données haute résolution pour la détection automatique des maladies de la vigne
2019
‘Flavescence dorée’ is a contagious and incurable disease present on the vine leaves. The DAMAV project (Automatic detection of Vine Diseases) aims to develop a solution for automated detection of vine diseases using a micro-drone. The goal is to offer a turnkey solution for wine growers. This tool will allow the search for potential foci, and then more generally any type of detectable vine disease on the foliage. To enable this diagnosis, the foliage is proposed to be studied using a dedicated high-resolution multispectral camera.The objective of this PhD-thesis in the context of DAMAV is to participate in the design and implementation of a Multi-Spectral (MS) image acquisition system and …
Evolutionary selection and variation in family businesses
2011
PurposeThis qualitative study attempts to understand what kinds of evolutionary selection and variation occur in family businesses during the preparation of a managerial and ownership succession.Design/methodology/approachThe study was conducted by interviewing members of one family business in Louisiana, USA and one in Finland in order to contribute to the understanding of succession preparation in small family businesses with two generations. Evolutionary economics was adapted for this interdisciplinary study to explain evolutionary changes in a family business succession.FindingsThe findings indicate that both selection and variation can take place through different routes during the pre…
A comparison of three recent selection theorems
2007
We compare a recent selection theorem given by Chistyakov using the notion of modulus of variation, with the Schrader theorem based on bounded oscillation and with the Di Piazza-Maniscalco theorem based on bounded ${\cal A},\Lambda$-oscillation.