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14 661 (0,107s)

Result

Boosted Surrogate Models in Evolutionary Optimization

modelling with regression boosting is proposed.

IN - Informatika

  • 2009
  • D
Result

Classification and Regression Forests.

. Similarly, a regression forest consists of several regression trees, and the overall regression function is defined as a weighted average of regression functions of bagging, boosting, arcing and Random F...

BA - Obecná matematika

  • 2004
  • D
Result

Machine-Learning-Assisted Prediction of Maximum Metal Recovery from Spent Zinc-Manganese Batteries

among five machine learning models, namely, linear regression, random forest regression, AdaBoost regression, gradient boosting regression and XG boost regression error and median error....

Mechanical engineering

  • 2022
  • Jimp
  • Link
Result

A comparative study of land subsidence susceptibility mapping of Tasuj plane, Iran, using boosted regression tree, random forest and classification and regression tree methods

) using boosted regression tree (BRT), random forest (RF), and classification and regression tree (CART) approaches with twelve influencing variables, namely altitude......

Environmental sciences (social aspects)

  • 2020
  • Jimp
  • Link
Result

Explanation and Probabilistic Prediction of Hydrological Signatures with Statistical Boosting Algorithms

predictions of hydrological signatures using statistical boosting in a regression setting is formulated as a regression problem, where the attributes are the predictor variables scores. We also exploit the statistical ...

Hydrology

  • 2021
  • Jimp
  • Link
Result

Boosted Regression Forest for the Doubly Trained Surrogate Covariance Matrix Adaptation Evolution Strategy

with the boosted regression forest, another regression model capable to estimate the distribution. Results of testing regression forest and Gaussian processes, the former in 20 be very expensive or time...

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

  • 2018
  • D
  • Link
Result

Boosted Regression Forest for the Doubly Trained Surrogate Covariance Matrix Adaptation Evolution Strategy

with the boosted regression forest, another regression model capable to estimate the distribution. Results of testing regression forest and Gaussian processes, the former in 20 be very expensive or time-consuming....

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

  • 2018
  • D
  • Link
Result

Accurate Estimation of Tensile Strength of 3D Printed Parts Using Machine Learning Algorithms

) used to estimate the tensile strength of 3D printed objects: (1) linear regression, (2) random forest regression, (3) AdaBoost regression, (4) gradient boosting regression, and (5) XGBoost regression...

Mechanical engineering

  • 2022
  • Jimp
  • Link
Result

Sequential model building in symbolic regression

Symbolic Regression is a supervised learning technique for regression based on Genetic Programming. A popular algorithm is the Multi-Gene Genetic Programming which by the Sequential Symbolic Regression algorithm, which buil...

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

  • 2019
  • D
  • Link
Result

A Comparative Analysis of Machine Learning Models in Prediction of Mortar Compressive Strength

, a comprehensive comparison of nine ML algorithms, i.e., linear regression (LR), random forest regression (RFR), support vector regression (SVR), AdaBoost regression (ABR), multi-layer perceptron (MLP), gradient <...

Mechanical engineering

  • 2022
  • Jimp
  • Link
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