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The use of information and information gain in the analysis of attribute dependencies

100%
Moliński K., Dobek A., Tomaszyk K.
Biometrical Letters
|
2012
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tom 49
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nr 2
149-158
EN
This paper demonstrates the possible conclusions which can be drawn from an analysis of entropy and information. Because of its universality, entropy can be widely used in different subjects, especially in biomedicine. Based on simulated data the similarities and differences between the grouping of attributes and testing of their independencies are shown. It follows that a complete exploration of data sets requires both of these elements. A new concept introduced in this paper is that of normed information gain, allowing the use of any logarithm in the definition of entropy.
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An evaluation of the efficiency of plant protection products via nonlinear statistical methods – a simulation study

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Skotarczak E., Bakinowska E., Tomaszyk K.
Biometrical Letters
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2014
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tom 51
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nr 2
171-179
EN
A nonlinear statistical approach was used to evaluate the efficiency of plant protection products. The methodology presented can be implemented when the observations in an experiment are recorded as success or failure. This occurs, for example, when following the application of a herbicide or pesticide, a single weed or insect is classified as alive (failure) or dead (success). Then a higher probability of success means a higher efficiency of the tested product. Using simulated data sets, a comparison was made of three methods based on the logit, probit and threshold models, with special attention to the effect of sample size and number of replications on the accuracy of the estimation of probabilities.
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