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16 461 (0,095s)

Result

Evolving Non-Linear Stacking Ensembles for Prediction of Go Player Attributes

The paper presents an application of non-linear stacking ensembles for prediction of Go player attributes. An evolutionary algorithm is used to form a diverse ensemble of base learners, which are then aggregated by a st...

IN - Informatika

  • 2015
  • D
  • Link
Result

Antenna contactless partial discharges detection in covered conductors using ensemble stacking neural networks

algorithms for this problem and the application of heterogeneous stacking ensembles using. The algorithm we propose is based on a stacking ensemble with a novel combination of base detection method and also introd...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2023
  • Jimp
  • Link
Result

Mapping changes of grassland to arable land using automatic machine learning of stacked ensembles and H2O library

stacked ensembles for mapping changes from grasslands to arable lands. All results the ROC curve (0.94-0.98). Stacked ensembles appear to be the most accurate machine......

Physical geography

  • 2024
  • Jimp
  • Link
Result

Hybrid soft computing methods for prediction of oil prices

This paper aims to provide combination of multiple prediction models using different strategies including ensemble selection, voting, stacking and multi-schemes to design a model capable of predicting oil prices accurately. Daily da...

IN - Informatika

  • 2015
  • D
  • Link
Result

The Best of Two Worlds: Using Stacked Generalisation for Integrating Expert Range Maps in Species Distribution Models

expert range maps in SDMs based on an ensemble method called stacked generalisation facilitating the use of algorithm ensembles. In addition, it provides a novel, data-driven distributions, while our work highlights the ov...

Zoology

  • 2024
  • Jimp
  • Link
Result

Ensemble Nonlinear Support Vector Machine Approach for Predicting Chronic Kidney Diseases

is formulated using ensemble nonlinear support vector machines and random forests. Thus work creates nonlinear combinations of kernel activations in prototype examples. Furthermore, different descriptors are combined in an...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2022
  • Jimp
  • Link
Result

Hybrid Levenberg–Marquardt and Weak-Constraint Ensemble Kalman Smoother Method

The ensemble Kalman smoother (EnKS) is used as a linear least-squares solver in the Gauss-Newton method for the large nonlinear least-squares system in incremental 4DVAR. The ensemble approach is naturally parallel over the...

IN - Informatika

  • 2016
  • Jx
  • Link
Result

Sentimental Analysis of COVID-19 Related Messages in Social Networks by Involving an N-Gram Stacked Autoencoder Integrated in an Ensemble Learning Scheme

-gram stacked encoder integrated in an ensemble machine learning scheme outperforms developed research involving ensemble deep learning techniques to reach a better that do the same. First, feature extraction is performed t...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2021
  • Jimp
  • Link
Result

A blending ensemble learning model for crude oil price forecasting

of crude oil. Specifically, a forecasting model is developed using blended ensemble are used to validate the proposed blending ensemble learning approach. To show individual and ensemble learning methods used for predictin...

Finance

  • 2025
  • Jimp
  • Link
Result

Robust Radio Frequency Fingerprinting with Signal Denoising and Stacked Multivariate Ensemble Learning for Secure Wireless Communications

-Golay Filtering (SGF) with Stacked Multivariate Ensemble Learning (SMvEL...

Telecommunications

  • 2025
  • Jimp
  • Link
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