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Sobre o processo de seleção de subconjuntos de atributos - as abordagens filtro e wrapper
(Universidade Federal de São Carlos, 2005-04-28) Santoro, Daniel Monegatto; Nicoletti, Maria do Carmo; https://lattes.cnpq.br/6454154048263145
Inductive machine learning methods learn the expression of the concept from a training set. Training sets are, generally, composed by instances described by attributevalue pairs and an associated class. The attribute set used for describing the training instances has a strong impact on the induced concepts. In a machine learning environment, attribute subset selection techniques aim at the identification of the attributes which effectively contribute for establishing the class of an instance. These techniques can be characterized as wrappers (if they are associated with a specific machine learning method) or filter and many of them work in conjunction with a search method (there are also embedded feature selection methods, not very representative). This work approaches the attribute subset selection problem by investigating the performance of two families of wrappers the NN (Nearest Neighbor) and DistAl families and three filter families Relief, Focus and LVF. The many members of the NN family (as well as of the DistAl family) differ among themselves with relation to the search method they use. The work presents and discusses the experiments conducted in many knowledge domains and their results allow a comparative evaluation (as far as accuracy and dimensionality are concerned) among the members of the families.
Macroinvertebrados da fitofauna de Eichhornia azurea (Swartz) Kunth em duas lagoas marginais do Rio Mogi- Guaçu (Estação Ecológica do Jataí, Luíz Antônio, SP, Brasil) / Mario André de Jancsó
(Universidade Federal de São Carlos, 2005-04-28) Jancso, Mário André de; Strixino, Susana Trivinho; https://lattes.cnpq.br/1804083229761186; https://lattes.cnpq.br/8605997915166172
In this study is analyzed the phytophilic Chironomidae assemblages of Eichhornia azurea (Swartz) Kunth in two ox-bow lakes (Diogo Lake and Óleo Lake) of the Mogi Guaçu s flood plain (Estação Ecológica de Jataí, Luíz Antônio, SP, Brazil). The colletion of E. azurea in both lakes were done during two seasons (rain season Nov./2002, Jan./2003, Mar./2003; dry season May/2003, Jul/2003, Oct/2003). From each lake 5 samples were randomly taken (3 were divided into 3 modules and separated the roots from the leafs and 2 were designated to estimate the adults emergency). However the richness and the numeric density were almost the same, the Chironomidae assemblage in the two lakes presented different faunistic arrangements (Psc < 60%), where the tribe Chironomini contributed with more than 20% of the fauna in both lakes. In Diogo Lake, Stenochironomus sp. was the dominant taxon as long as Goeldichironomus spp.> Polypedilum (Asheum) sp. > Beardius sp. were the most abundant taxa in Óleo Lake. These differences exhibited on the macroinvertebrates distribution among the modules and between the macrophyte parts. Diogo Lake had the fauna almost equally distributed on the modules and parts while in Óleo Lake there was a concentration of larvae on the roots and numerical distribution following the age s vegetable gradient. There wasn t observed direct influence of the river s hydrologic cycle on the macroinvertebrates dynamic however it were more numerous during the dry season (Diogo Lake); Óleo Lake presented no differences between the dry and the rain season. The adults (Chironomidae) presented different season pattern in the two lakes. In Óleo Lake, Tanytarsini and Chironomini concentrated its emergency during the rain season; in Diogo Lake just Tanytarsini showed higher emergency in the rain season. The observed differences between the macroinvertebrate assemblages are probably related with the macrophytes density and the morfometric characteristics of these two ox-bow lakes.