Recent advances in decision trees: An updated survey

VG Costa, CE Pedreira - Artificial Intelligence Review, 2023 - Springer
Abstract Decision Trees (DTs) are predictive models in supervised learning, known not only
for their unquestionable utility in a wide range of applications but also for their interpretability …

Artificial intelligence in cancer target identification and drug discovery

Y You, X Lai, Y Pan, H Zheng, J Vera, S Liu… - … and Targeted Therapy, 2022 - nature.com
Artificial intelligence is an advanced method to identify novel anticancer targets and discover
novel drugs from biology networks because the networks can effectively preserve and …

Generalized divergence-based decision making method with an application to pattern classification

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Y Wu, Y Ke, Z Chen, S Liang, H Zhao, H Hong - Catena, 2020 - Elsevier
Landslides are a common type of natural disaster that brings great threats to the human lives
and economic development around the world, especially in the Chinese Loess Plateau …

A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran

K Khosravi, BT Pham, K Chapi, A Shirzadi… - Science of the Total …, 2018 - Elsevier
Floods are one of the most damaging natural hazards causing huge loss of property,
infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due …

Multi-objective hub-spoke network design of perishable tourism products using combination machine learning and meta-heuristic algorithms

AP Chobar, MA Adibi, A Kazemi - Environment, Development and …, 2022 - Springer
In this research, the objective is to design a multi-objective Hub-Spoke network of perishable
tourism products. In order to consider the perishable factor of the products, some collection …

Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science

A Agrawal, A Choudhary - Apl Materials, 2016 - pubs.aip.org
Our ability to collect “big data” has greatly surpassed our capability to analyze it,
underscoring the emergence of the fourth paradigm of science, which is datadriven …

Modeling flood susceptibility using data-driven approaches of naïve bayes tree, alternating decision tree, and random forest methods

W Chen, Y Li, W Xue, H Shahabi, S Li, H Hong… - Science of The Total …, 2020 - Elsevier
Floods are one of the most devastating types of disasters that cause loss of lives and
property worldwide each year. This study aimed to evaluate and compare the prediction …