1,721,100 research outputs found
Modelli Semiparametrici di Classificazione e Regressione Supervisionata: Alcune Proposte di Integrazione e Procedure di Stima
No full text
Interactive visualization in multiclass learning: integrating the SASSC algorithm with KLIMT
No full textClassification, Multiclass response, Subset selection, Semi-supervised learning, CART, SASSC, Phylogenetic tree, KLIMT, Interactive visualization,
Bagged Mixtures of Classifiers using Model Scoring Criteria
No full textIn the context of supervised statistical learning, we present a broad class of models named Generalised Additive Multi-Mixture Models (GAM-MM), based on a multiple combination of mixtures of classifiers to be used in both the regression and classification cases. In particular, we additively combine mixtures of different types of classifiers, defining an ensemble composed of nonparametric tools (tree- based methods), semiparametric tools (scatterplot smoothers) and parametric tools (linear regression). Within this approach, we define a classifier scoring criterion to be jointly used with the bagging procedure for estimation of the mixing parameters, and describe the GAM- MM estimation procedure, that adaptively works by iterating a backfitting-like algorithm and a local scoring procedure until convergence. The effectiveness of our approach in modelling complex data structures is evaluated by presenting the results of some applications on real and simulated data
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