Results 41 to 50 of about 3,227,878 (310)
, 2023 The wealth of data being gathered about humans and their surroundings drives new machine learning applications in various fields. Consequently, more and more often, classifiers are trained using not only numerical data but also complex data objects. For example, multi-omics analyses attempt to combine numerical descriptions with distributions, time ...
Maciej Piernik +2 more
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Random Forest Algorithm for Differential Privacy Protection [PDF]
Jisuanji gongcheng, 2020 Privacy protection in data mining is one of the research hotspots in the field of information security.To address the classification problem under privacy protection requirements,this paper proposes a random forest algorithm RFDPP-Gini for differential ...
LI Yuanhang, CHEN Xianlai, LIU Li, AN Ying, LI Zhongmin
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Pilar Nusa Mandiri, 2022 This study predicts and classifies benign and malignant breast cancer using 3 classification models. The method used in this research is Random Forest, Naïve Bayes and AdaBoost.
Bahtiar Imran +5 more
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On Oblique Random Forests [PDF]
, 2011 In his original paper on random forests, Breiman proposed two different decision tree ensembles: one generated from "orthogonal" trees with thresholds on individual features in every split, and one from "oblique" trees separating the feature space by randomly oriented hyperplanes.
Bjoern H. Menze +4 more
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Multimodal random forest based tensor regression
IET Computer Vision, 2014 This study presents a method, called random forest based tensor regression, for real‐time head pose estimation using both depth and intensity data. The method builds on random forests and proposes to train and use tensor regressors at each leaf node of ...
Sertan Kaymak, Ioannis Patras
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Random forest-based track initiation method
The Journal of Engineering, 2019 In this study, a novel method based on the random forest is presented to solve the problem of track initiation in the air-traffic-control (ATC) radar system. ATC radar is the most common civilian surveillance radar. There are dense targets with different
Shuo Liu +4 more
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A Multi-Task Framework for Action Prediction
Information, 2020 Predicting the categories of actions in partially observed videos is a challenging task in the computer vision field. The temporal progress of an ongoing action is of great importance for action prediction, since actions can present different ...
Tianyu Yu +3 more
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Knowledge-Based SystemsThe Random Forest (RF) classifier is often claimed to be relatively well calibrated when compared with other machine learning methods. Moreover, the existing literature suggests that traditional calibration methods, such as isotonic regression, do not substantially enhance the calibration of RF probability estimates unless supplied with extensive ...
Shaker, Mohammad Hossein +1 more
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Generalized random forests [PDF]
The Annals of Statistics, 2019 We propose generalized random forests, a method for non-parametric statistical estimation based on random forests (Breiman, 2001) that can be used to fit any quantity of interest identified as the solution to a set of local moment equations. Following the literature on local maximum likelihood estimation, our method considers a weighted set of nearby ...
Athey, Susan +2 more
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IEEE Access, 2022 Random forests of axis-parallel decision trees still show competitive accuracy in various tasks; however, they have drawbacks that limit their applicability. Namely, they perform poorly for multidimensional sparse data. A straightforward solution is to create forests of decision trees with oblique splits; however, most training approaches have low ...
Dmitry Devyatkin, Oleg G. Grigoriev
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