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Predicting the Accuracy of Ligand Overlay Methods with Random Forest Models
Journal of Chemical Information and Modeling, 2008The accuracy of binding mode prediction using standard molecular overlay methods (ROCS, FlexS, Phase, and FieldCompare) is studied. Previous work has shown that simple decision tree modeling can be used to improve accuracy by selection of the best overlay template.
Ravi Nandigam +4 more
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Density estimation via the random forest method
Communications in Statistics - Theory and Methods, 2017AbstractThe problem of density estimation arises naturally in many contexts. In this paper, we consider the approach using a piecewise constant function to approximate the underlying density. We present a new density estimation method via the random forest method based on the Bayesian Sequential Partition (BSP) (Lu et al., 2013).
Kaiyuan Wu, Wei Hou, Hongbo Yang
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A hierarchical method for pedestrian detection with random forests
2014 12th International Conference on Signal Processing (ICSP), 2014Due to many uncontrolled factors, pedestrian detection is one of the most challenging problems in computer vision. In this paper, a fast and accurate hierarchical method for pedestrian detection with random forests is proposed, which can combine holistic information and local information based on image pyramid model.
Tao Xiang +4 more
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A fault diagnosis method of engine rotor based on Random Forests
2016 IEEE International Conference on Prognostics and Health Management (ICPHM), 2016Rotor is the main part of the engine, the vibration fault is very common in the process of running, it must be monitored, checked, excluded in a timely manner for improving the reliability of engine and aircraft safety. This paper mainly studies four kinds of rotor fault, including unbalance, misalignment, surge, bearing failure. The frequency spectrum
Qi Yao +4 more
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Adaptive method for complete random forest
Second International Conference on Industrial IoT, Big Data, and Supply Chain, 2021Yong Zheng, Shuyin Xia, Qun Liu
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Investigation of Random Subspace and Random Forest Methods Applied to Property Valuation Data
2011The experiments aimed to compare the performance of random subspace and random forest models with bagging ensembles and single models in respect of its predictive accuracy were conducted using two popular algorithms M5 tree and multilayer perceptron.
Tadeusz Lasota +2 more
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Sleep Stage Classification Using Random Forest Method
Proceedings of the 12th International Conference on Biomedical Engineering and Technology, 2022Yazan M. Dweiri +3 more
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Malignant Brain Tumor Classification Using the Random Forest Method
2018Brain tumor grading is pivotal in treatment planning. Contrast-enhanced T1-weighted MR image is commonly used for grading. However, the classification of different types of high-grade gliomas using T1-weighted MR images is still challenging, due to the lack of imaging biomarkers.
Zhang, Lichi +5 more
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Rotation Forest and Random Oracles: Two Classifier Ensemble Methods
Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS'07), 2007Classification methods are widely used in computer-based medical systems. Often, the accuracy of a classifier can be improved using a classifier ensemble, the combination of several classifiers. Two classifiers ensembles and their results on several medical data sets will be presented: Rotation Forest (Rodriguez, Kuncheva and Alonso) and Random Oracles
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Unsupervised Entity Resolution Method Based on Random Forest
2021Wanying Xu +4 more
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