Search alternatives:
forest classification » text classification (Expand Search), risk classification (Expand Search), disease classification (Expand Search)
based optimization » whale optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data forest » data first (Expand Search), data formats (Expand Search)
binary made » binary image (Expand Search), binary mask (Expand Search)
made based » image based (Expand Search)
forest classification » text classification (Expand Search), risk classification (Expand Search), disease classification (Expand Search)
based optimization » whale optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data forest » data first (Expand Search), data formats (Expand Search)
binary made » binary image (Expand Search), binary mask (Expand Search)
made based » image based (Expand Search)
-
1
-
2
Model 1: All Variables for binary classification.
Published 2025“…Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. …”
-
3
-
4
-
5
Integrative Clinical and Bio-mechanical Features Predict In-Hospital Trauma Mortality
Published 2024Subjects: -
6
Class distribution for binary classes.
Published 2025“…Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. …”
-
7
Algorithm for generating hyperparameter.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
-
8
-
9
Random forest algorithm: Method and example results.
Published 2019“…(<b>D</b>) Schematic illustration of arrays input into Random Forest algorithm. Columns correspond to gene, rows to pixels in the top projection data set. …”
-
10
Results of machine learning algorithm.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
-
11
ROC comparison of machine learning algorithm.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
-
12
ML algorithms used in this study.
Published 2025“…Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. …”
-
13
Data Sheet 1_Bundled assessment to replace on-road test on driving function in stroke patients: a binary classification model via random forest.docx
Published 2025“…The subject was classified as either Success or Unsuccess group according to whether they had completed the on-road test. A random forest algorithm was then applied to construct a binary classification model based on the data obtained from the two groups.…”
-
14
-
15
Best optimizer results of Lightbgm.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
-
16
Best optimizer results of Adaboost.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
-
17
Best optimizer results of Lightbgm.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
-
18
Random forest with hyperparameter optimization.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
-
19
Best optimizer results of KNN.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
-
20
Best optimizer results of KNN.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”