Hyper-parameter tuned light gradient boosting machine using memetic firefly algorithm for hand gesture recognition

TL;DR: A comprehensive and updated survey of wearable devices for sEMG detection, both reported in the scientific literature and on the market, is provided, mainly applied in rehabilitation training and physiological tracking as mentioned in this paper .

TL;DR: In this paper , the authors proposed a tree-structured parzen estimator (TPE) model with light gradient boosting machine (LightGBM) model to predict heating and cooling loads in residential buildings.

TL;DR: In this article , the authors proposed a novel hybrid MFO-XGBoost model that integrates the moth-flame optimization (MFO) algorithm and the extreme gradient boosting (XGBOost) to predict the racking ratio of rectangular tunnels subjected to seismic loading.

TL;DR: In this paper, an optimal fault-tolerant pitch control (FTPC) strategy is addressed to adjust the pitch angle of WT blades in the presence of sensor, actuator, and system faults.

TL;DR: A general gradient descent boosting paradigm is developed for additive expansions based on any fitting criterion, and specific algorithms are presented for least-squares, least absolute deviation, and Huber-M loss functions for regression, and multiclass logistic likelihood for classification.

TL;DR: XGBoost as discussed by the authors proposes a sparsity-aware algorithm for sparse data and weighted quantile sketch for approximate tree learning to achieve state-of-the-art results on many machine learning challenges.

TL;DR: It is proved that, since the data instances with larger gradients play a more important role in the computation of information gain, GOSS can obtain quite accurate estimation of the information gain with a much smaller data size, and is called LightGBM.