Results 11 to 20 of about 839,459 (306)
Endogenous Mechanisms of Neuroprotection: To Boost or Not to Be [PDF]
Cells, 2021 Postmitotic cells, like neurons, must live through a lifetime. For this reason, organisms/cells have evolved with self-repair mechanisms that allow them to have a long life. The discovery workflow of neuroprotectors during the last years has focused on blocking the pathophysiological mechanisms that lead to neuronal loss in neurodegeneration ...
Sara Marmolejo-Martínez-Artesero +2 more
openaire +4 more sources
To Boost or not to Boost: On the Limits of Boosted Neural Networks
CoRR, 2021 Boosting is a method for finding a highly accurate hypothesis by linearly combining many ``weak" hypotheses, each of which may be only moderately accurate. Thus, boosting is a method for learning an ensemble of classifiers. While boosting has been shown to be very effective for decision trees, its impact on neural networks has not been extensively ...
Sai Saketh Rambhatla +2 more
openaire +2 more sources
To boost or not to boost? On the limits of boosted trees for object detection [PDF]
2016 23rd International Conference on Pattern Recognition (ICPR), 2016 ICPR, December 2016. Added WIDER FACE test results (Fig. 5)
Eshed Ohn-Bar, Mohan M. Trivedi
openaire +2 more sources
LDA boost classification: boosting by topics [PDF]
EURASIP Journal on Advances in Signal Processing, 2012 AdaBoost is an efficacious classification algorithm especially in text categorization (TC) tasks. The methodology of setting up a classifier committee and voting on the documents for classification can achieve high categorization precision. However, traditional Vector Space Model can easily lead to the curse of dimensionality and feature sparsity ...
Lei La, Qiao Guo, Qimin Cao, Qitao Li
openaire +1 more source
Boosted horizon of a boosted spacetime geometry [PDF]
The Fourteenth Marcel Grossmann Meeting, 2017 prepared for the ES3 (Exact Solutions (Physical Aspects)) session of the MG14 Conference, Rome, July ...
BATTISTA E +3 more
openaire +3 more sources
MPSUBoost: A Modified Particle Stacking Undersampling Boosting Method
IEEE Access, 2022 Class imbalance problems are prevalent in the real world. In such cases, traditional supervised algorithms tend to have difficulty in recognizing minority data because the models are likely to maximize prediction accuracy by simply ignoring minority data.
Sang-Jin Kim, Dong-Joon Lim
doaj +1 more source
Gradient boosting to boost the efficiency of hydraulic fracturing [PDF]
Journal of Petroleum Exploration and Production Technology, 2019 In this paper, we present a data-driven model for forecasting the production increase after hydraulic fracturing (HF). We use data from fracturing jobs performed at one of the Siberian oilfields. The data includes features, characterizing the jobs, and geological information.
Ivan Makhotin +2 more
openaire +3 more sources
Cumhuriyet Science Journal, 2020 The purpose of this study is to classify the data set which is created by taking students who placed to universities from 81 provinces, in accordance with Undergraduate Placement Examination between the years 2010-2013 in Turkey, with Bagging and ...
Tuğba Tuğ Karoğlu, Hayrettin Okut
doaj +1 more source
Remote Sensing, 2021 In recent years, several powerful machine learning (ML) algorithms have been developed for image classification, especially those based on ensemble learning (EL).
Hamid Jafarzadeh +4 more
doaj +1 more source
Regression Models for Symbolic Interval-Valued Variables
Entropy, 2021 This paper presents new approaches to fit regression models for symbolic internal-valued variables, which are shown to improve and extend the center method suggested by Billard and Diday and the center and range method proposed by Lima-Neto, E.A.and De ...
Jose Emmanuel Chacón +1 more
doaj +1 more source