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Experiments with adabag in biology classification tasks

Authors

Fernández-Delgado M. , Cernadas E. , PÉREZ ORTIZ, MARÍA

External publication

No

Means

Ensemble Classification Methods with Applications in R

Scope

Capítulo de un Libro

Nature

Científica

JCR Quartile

SJR Quartile

Publication date

01/01/2018

Scopus Id

2-s2.0-85104759434

Abstract

The assessment of fecundity is fundamental in the study of biology and to define the management of sustainable fisheries. Stereometry is an accurate method to estimate fecundity from histological images. This chapter shows some histological images of fish species Merluccius merluccius. The direct kernel perceptron (DKP) is a very simple and fast kernel-based classifier, whose trainable parameters are calculated directly, without any iterative training, using an analytical closed-form expression that involves only the training patterns and the classes to which they belong. An accurate fish fecundity estimation must only consider mature oocytes, which must be reliably classified, according to their stage of development, by experienced personnel using histological images. The fish oocytes were manually drawn and labelled with the development stage by expert technicians of the Institute of Marine Research CSIC using Govocitos software. Adaboost.M1 in Weka (ABW) is much worse than the Adabag version in all the species and experiments. © 2019 John Wiley & Sons, Ltd.

Keywords

Direct kernel perceptron; Fecundity assessment; Govocitos software; Kernel-based classifier; Stereometry; Sustainable fisheries management