Exact(7)
We propose a boosting algorithm for training the detector nodes.
This paper presents a novel boosting algorithm for genetic learning of fuzzy classification rules.
It uses multi-block local binary pattern features and the boosting algorithm for face detection [9].
The most commonly used boosting algorithm for classification is AdaBoost [9].
To extend the results obtained in (Oduro et al. 2014), we propose to use a boosting algorithm for improving the performance of MARS model.
Boost and Bag models indicate models trained using the standard boosting and bagging algorithm, respectively, on the phoneme classification task, while E-boost indicates the expectation boosting algorithm for word error rate minimisation.
Similar(53)
Strom [ 7] reported a genetic programming (GP) method with boosting algorithms for the binary classification of effective and ineffective siRNAs.
For instance, an effective similarity oriented boosting algorithm is proposed for iris recognition inspired by the similarity property of the training samples.
The tested models, i.e., the Cox regression model containing the conventional markers alone and the three different feature selection models (the Lasso and Ridge regressions and the C-index boosting algorithm) were evaluated for their predictive accuracies (generalizabilities) using the deviance from the null model and iRBS.
In this study, cost-sensitive boosting algorithm is firstly introduced for solving serious imbalance samples and building prediction models.
Section 3 proposes the LDA-based boosting algorithm operating on MPCA features for enhancing gait recognition performance.
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