Bagging, boosting and Random Forests are classical ensemble methods used to improve the performance of single classifiers. They obtain superior performance by increasing the accuracy and diversity of the single classifiers. Attempts have been made to reproduce these methods in the more challenging context of evolving data streams. In this paper, we propose a new variant of bagging, called lever...

Various approaches to extend bagging ensembles for class imbalanced data are considered. First, we review known extensions and compare them in a comprehensive experimental study. The results show that integrating bagging with under-sampling is more powerful than over-sampling. They also allow to distinguish Roughly Balanced Bagging as the most accurate extension. Then, we point out that complex...

Classifiers built on small training sets are usually biased or unstable. Different techniques exist to construct more stable classifiers. It is not clear which ones are good, and whether they really stabilize the classifier or just improve the performance. In this paper bagging (bootstrapping and aggregating (1)) is studied for a number of linear classifiers. A measure for the instability of cl...

In this paper we present an improvement of the precision of classification algorithm results. Two various approaches are known: bagging and boosting. This paper describes a set of experiments with bagging and boosting methods. Our use of these methods aims at classification algorithms generating decision trees. Results of performance tests focused on the use of the bagging and boosting methods ...

Bagging is one of the older, simpler and better known ensemble methods. However, the bootstrap sampling strategy in bagging appears to lead to ensembles of low diversity and accuracy compared with other ensemble methods. In this paper, a new variant of bagging, named IGF-Bagging, is proposed. Firstly, this method obtains bootstrap instances. Then, it employs Information Gain (IG) based feature ...

Abstract This paper aims to study the mechanical properties of hybrid polymer composites and addition primary secondary fillers nano-aluminum oxide nanographene Kenaf epoxy composites. The vacuum bagging method was used fabricate advantage using is reduce blowholes. weight ratio fiber 50%–60%, matrix 40%, 0%–6%, 0%–3% considered. Mechanical like Tensile strength, Young’s modulus elongation, fle...

Tomato borers, especially Tuta absoluta (Lepidoptera: Gelechiidae), a pest introduced in southern Europe, northern Africa and the Middle East, and diseases can damage tomato (Solanum lycopersicum) fruit. This study tested the economic and technical feasibility of bagging tomato fruits clusters during organic production to protect them against insects and diseases. The experiment was randomized ...

Tujuan dari penelitian ini untuk mengetahui kekuatan sifat mekanik dan fisik komposit sandwich carbon fiber core kayu balsa dengan variasi jumlah layer skin (2, 4, 6 ), orientasi serat (0°/90°) ketebalan 5 mm. Matriks yang digunakan adalah resin epoxy bakelite EPR 174 manufaktur menggunakan metode hand lay-up vacuum bagging , dimana standar spesimen mengacu pada ASTM D790 pengujian bending D611...

In the regression context, boosting and bagging are techniques to build a committee of regressors that may be superior to a single regressor. We use regression trees as fundamental building blocks in bagging committee machines and boosting committee machines. Performance is analyzed on three non-linear functions and the Boston housing database. In all cases, boosting is at least equivalent, and...