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Boosted Tree Ensembles for Artificial Intelligence Based Automated Valuation Models (AI-AVM)

• Authors : Tien Foo Sing; Shi Ming Yu; Jesse Jingye Yang

Subjects: Economics and Econometrics; Boosting (machine learning); Housing markets

• Source: The Journal of Real Estate Finance and Economics

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Feature partitioning for robust tree ensembles and their certification in adversarial scenarios

• Authors : Calzavara, Stefano; Lucchese, Claudio; Marcuzzi, Federico

• Source: EURASIP Journal on Information Security ; volume 2021, issue 1 ; ISSN 2510-523X

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Interpreting tree ensembles with inTrees

• Authors : Houtao Deng

Subjects: FOS: Computer and information sciences; 0301 basic medicine; Computer science

• Source: International Journal of Data Science and Analytics. 7:277-287

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Network-based Biased Tree Ensembles (NetBiTE) for Drug Sensitivity Prediction and Drug Sensitivity Biomarker Identification in Cancer

• Authors : Oskooei, Ali; Manica, Matteo; Mathis, Roland

• Source: Scientific Reports ; volume 9, issue 1 ; ISSN 2045-2322

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Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique

• Authors : Derek Partridge; Jonathan E. Fieldsend; Vitaly Schetinin

Subjects: FOS: Computer and information sciences; Computer Science - Artificial Intelligence; business.industry

• Source: Journal of Mathematical Modelling and Algorithms. 5:397-416

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Predicting gene function using hierarchical multi-label decision tree ensembles

• Authors : Schietgat, Leander; Vens, Celine; Struyf, Jan

• Source: BMC Bioinformatics ; volume 11, issue 1 ; ISSN 1471-2105

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Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles

• Authors : Ge, Guangtao; Wong, G William

• Source: BMC Bioinformatics ; volume 9, issue 1 ; ISSN 1471-2105

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Network inference with ensembles of bi-clustering trees

• Authors : Celine Vens; Konstantinos Pliakos

Subjects: Databases, Factual; Computer science; Gene regulatory network

• Source: BMC BioinformaticsBMC Bioinformatics, Vol 20, Iss 1, Pp 1-12 (2019)

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Practical guidelines for the use of gradient boosting for molecular property prediction

• Authors : Boldini, Davide; Grisoni, Francesca; Kuhn, Daniel ...

• Source: Journal of Cheminformatics ; volume 15, issue 1 ; ISSN 1758-2946

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DeepTLF: robust deep neural networks for heterogeneous tabular data

• Authors : Borisov, Vadim; Broelemann, Klaus; Kasneci, Enkelejda ...

• Source: International Journal of Data Science and Analytics ; volume 16, issue 1, page 85-100 ; ISSN 2364-415X 2364-4168

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