Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...
AdaBoost.R2 regression is a machine learning technique used to predict a single numeric value. AdaBoost.R2 builds a sequence of decision tree regressors where each accepted tree improves prediction ...
Abstract: Accurate recognition of gestures based on surface EMG signals is of very importance in the study of human prosthetic interaction. In this paper, multi-feature combination and adaptive ...
A mobile ultrasonic stratified flow velocity measurement device, which utilizes a pair of ultrasonic transducers, was characterized by its low power consumption and the ability to measure multi-layer ...
Abstract: Boosting algorithms are widely used for predicting demand in bike-sharing systems (BSSs). However, these systems often encounter sudden spikes in demand (extreme demand). Ordinary boosting ...
ABSTRACT: This paper proposes an adaptive and diverse hybrid-based ensemble method to improve the performance of binary classification. The proposed method is a non-linear combination of base models ...
Your browser does not support the audio element. Neural networks and Genetic algorithms are our naive approach to imitate nature. They work well for a class of ...
Tree boosting has empirically proven to be efficient for predictive mining for both classification and regression. For many years, MART (multiple additive regression trees) has been the tree boosting ...
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