scholarly journals THE ENSEMBLE METHOD DEVELOPMENT OF CLASSIFICATION OF THE COMPUTER SYSTEM STATE BASED ON DECISIONS TREES

2020 ◽  
Vol 4 (3) ◽  
pp. 5-10
Author(s):  
Svitlana Gavrylenko ◽  
Illia Sheverdin ◽  
Michael Kazarinov
Keyword(s):  
Computer System ◽  
Method Development ◽  
Ensemble Method ◽  
System State ◽  
The Ensemble Method

Estimating Heterogeneous Treatment Effects and the Effects of Heterogeneous Treatments with Ensemble Methods

2017 ◽  
Vol 25 (4) ◽  
pp. 413-434 ◽  
Author(s):  
Justin Grimmer ◽  
Solomon Messing ◽  
Sean J. Westwood
Keyword(s):  
Treatment Effects ◽  
Ensemble Methods ◽  
Ensemble Method ◽  
Superior Performance ◽  
Accurate Estimation ◽  
Randomized Experiments ◽  
Heterogeneous Treatment Effects ◽  
Data Set ◽  
Heterogeneous Effects ◽  
The Ensemble Method

Randomized experiments are increasingly used to study political phenomena because they can credibly estimate the average effect of a treatment on a population of interest. But political scientists are often interested in how effects vary across subpopulations—heterogeneous treatment effects—and how differences in the content of the treatment affects responses—the response to heterogeneous treatments. Several new methods have been introduced to estimate heterogeneous effects, but it is difficult to know if a method will perform well for a particular data set. Rather than using only one method, we show how an ensemble of methods—weighted averages of estimates from individual models increasingly used in machine learning—accurately measure heterogeneous effects. Building on a large literature on ensemble methods, we show how the weighting of methods can contribute to accurate estimation of heterogeneous treatment effects and demonstrate how pooling models lead to superior performance to individual methods across diverse problems. We apply the ensemble method to two experiments, illuminating how the ensemble method for heterogeneous treatment effects facilitates exploratory analysis of treatment effects.

scholarly journals A Computer System for Classification of Burns and Determination of Fluid and Nutritional Needs for Burn Patients

2021 ◽  
Vol 3 (2) ◽  
pp. 1329-1341
Author(s):  
Safwat Ibrahim ◽  
Reda Abo-Alez ◽  
Fawzy Hamza ◽  
Lotfy Nassar ◽  
Esam Taman ◽  
...  
Keyword(s):  
Computer System ◽  
Burn Patients ◽  
Nutritional Needs

Acoustic Events Detection in Dissimilarity Measurement Space

2013 ◽  
Vol 333-335 ◽  
pp. 764-768
Author(s):  
Lin Bin Jia ◽  
Lin Li ◽  
Rong Nie
Keyword(s):  
Euclidean Distance ◽  
Ensemble Method ◽  
Feature Subset ◽  
Environmental Sounds ◽  
Detection Model ◽  
Svm Algorithm ◽  
Comparable Performance ◽  
The Ensemble Method ◽  
Events Detection ◽  
Ensemble Experiments

The paper considers the problem of detecting acoustic events in a robust manner. The dissimilarity measurement is used to measure the distance between acoustic samples. Then this distance is used as the replacement of the Euclidean distance to build the detection model with the SVM algorithm. All the well-known features are considered when we build model in a way of feature subset ensemble. Experiments are conducted to detect events under a variety of environmental sounds. The model demonstrates the robustness of the ensemble method with dissimilarity measurement. The detection model has shown to produce comparable performance as human listeners.

scholarly journals An ensemble method to predict target genes and pathways in uveal melanoma

2018 ◽  
Vol 13 (1) ◽  
pp. 90-96
Author(s):  
Chao Wei ◽  
Lei Wang ◽  
Han Zhang
Keyword(s):  
Uveal Melanoma ◽  
Target Genes ◽  
Pearson Correlation ◽  
Correlation Method ◽  
Enrichment Analysis ◽  
Ensemble Method ◽  
Borda Count ◽  
Pathway Enrichment Analysis ◽  
Mirna Targets ◽  
The Ensemble Method

AbstractObjectiveThis work proposes to predict target genes and pathways for uveal melanoma (UM) based on an ensemble method and pathway analyses. Methods: The ensemble method integrated a correlation method (Pearson correlation coefficient, PCC), a causal inference method (IDA) and a regression method (Lasso) utilizing the Borda count election method. Subsequently, to validate the performance of PIL method, comparisons between confirmed database and predicted miRNA targets were performed. Ultimately, pathway enrichment analysis was conducted on target genes in top 1000 miRNA-mRNA interactions to identify target pathways for UM patients. Results: Thirty eight of the predicted interactions were matched with the confirmed interactions, indicating that the ensemble method was a suitable and feasible approach to predict miRNA targets. We obtained 50 seed miRNA-mRNA interactions of UM patients and extracted target genes from these interactions, such as ASPG, BSDC1 and C4BP. The 601 target genes in top 1,000 miRNA-mRNA interactions were enriched in 12 target pathways, of which Phototransduction was the most significant one. Conclusion: The target genes and pathways might provide a new way to reveal the molecular mechanism of UM and give hand for target treatments and preventions of this malignant tumor.

Solder joint defect classification based on ensemble learning

2017 ◽  
Vol 29 (3) ◽  
pp. 164-170 ◽  
Author(s):  
Hao Wu
Keyword(s):  
Random Forest ◽  
Solder Joint ◽  
Decision Trees ◽  
Printed Circuit Board ◽  
Solder Joints ◽  
High Accuracy ◽  
Ensemble Method ◽  
Circuit Board ◽  
Content Type

Purpose This paper aims to inspect the defects of solder joints of printed circuit board in real-time production line, simple computing and high accuracy are primary consideration factors for feature extraction and classification algorithm. Design/methodology/approach In this study, the author presents an ensemble method for the classification of solder joint defects. The new method is based on extracting the color and geometry features after solder image acquisition and using decision trees to guarantee the algorithm’s running executive efficiency. To improve algorithm accuracy, the author proposes an ensemble method of random forest which combined several trees for the classification of solder joints. Findings The proposed method has been tested using 280 samples of solder joints, including good and various defect types, for experiments. The results show that the proposed method has a high accuracy. Originality/value The author extracted the color and geometry features and used decision trees to guarantee the algorithm's running executive efficiency. To improve the algorithm accuracy, the author proposes using an ensemble method of random forest which combined several trees for the classification of solder joints. The results show that the proposed method has a high accuracy.

scholarly journals Development of an Interdisciplinary Prediction System Combining Sediment Transport Simulation and Ensemble Method

Water ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 2588
Author(s):  
Hao-Che Ho ◽  
Yen-Ming Chiang ◽  
Che-Chi Lin ◽  
Hong-Yuan Lee ◽  
Cheng-Chia Huang
Keyword(s):  
Sediment Transport ◽  
Numerical Modelling ◽  
Ensemble Method ◽  
River Morphology ◽  
River Channels ◽  
Ensemble Size ◽  
Transport Simulation ◽  
Bed Elevation ◽  
The Ensemble Method ◽  
Simulation Time

The change in movable beds is related to the mechanisms of sediment transport and hydrodynamics. Numerical modelling with empirical equations and the simplified momentum equation is the common means to analyze the complicated sediment transport processing in river channels. The optimization of parameters is essential to obtain the proper results. Inadequate parameters would cause errors during the simulation process and accumulate the errors with long-time simulation. The optimized parameter combination for numerical modelling, however, is rarely discussed. This study adopted the ensemble method to simulate the change in the river channel, with a single model combined with multiple parameters. The optimized parameter combinations for a given river reach are investigated. Two river basins, located in Taiwan, were used as study cases, to simulate river morphology through the SRH-2D, which was developed by the U.S. Bureau of Reclamation. The input parameters related to the sediment transport module were randomly selected within a reasonable range. The parameter sets with proper results were selected as ensemble members. The concentration of sedimentation and bathymetry elevation was used to conduct the calibration. Both study cases show that 20 ensemble members were good enough to capture the results and save simulation time. However, when the ensemble members increased to 100, there was no significant improvement, but a longer simulation time. The result showed that the peak concentration and the occurrence of time could be predicted by the ensemble size of 20. Moreover, with consideration of the bed elevation as the target, the result showed that this method could quantitatively simulate the change in bed elevation. With both cases, this study showed that the ensemble method is a suitable approach for river morphology numerical modelling. The ensemble size of 20 can effectively obtain the result and reduce the uncertainty for sediment transport simulation.

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