Results 81 to 90 of about 686,580 (270)
Multiple thresholds and trajectories of microbial biodiversity predicted across browning gradients by neural networks and decision tree learning. [PDF]
ISME Commun, 2021 Fontaine L +6 more
europepmc +1 more source
State‐of‐the‐Art, Insights, and Perspectives for MOFs‐Nanocomposites and MOF‐Derived (Nano)Materials
Advanced Materials, EarlyView.Different approaches to MOF‐NP composite formation, such as ship‐in‐a‐bottle, bottle‐around‐the‐ship and in situ one‐step synthesis, are used. Owing to synergistic effects, the advantageous features of the components of the composites are beneficially combined, and their individual drawbacks are mitigated.
Stefanos Mourdikoudis +6 more
wiley +1 more source
Learning kμ decision trees on the uniform distribution [PDF]
, 1993 Thomas R. Hancock
openalex +1 more source
Machine‐Learning‐Aided Advanced Electrochemical Biosensors
Advanced Materials, EarlyView.Electrochemical biosensors are highly sensitive, portable, and versatile. Advanced nanomaterials enhance their performance, while machine learning (ML) improves data analysis, minimizes interference, and optimizes sensor design. Despite progress in both fields, their combined potential in diagnostics remains underexplored.
Andrei Bocan +9 more
wiley +1 more source
Advanced Materials, EarlyView.Reversible protonic ceramic electrochemical cells (R‐PCECs) face challenges from sluggish and unstable oxygen reduction and evolution reactions in the air electrode. This review discusses recent progress in triple‐conducting air electrodes, emphasizing mechanisms, performance factors, and design strategies, offering guidance for creating efficient and ...
Xi Chen +8 more
wiley +1 more source
Multitarget Generate Electrolyte Additive for Lithium Metal Batteries
Advanced Materials, EarlyView.This study presents a deep learning‐assisted generative model for electrolyte additives in lithium metal batteries (LMBs). The approach overcomes data scarcity by proposing the molecular categorization method and achieves 100% generative efficiency.
Xiangyang Liu +12 more
wiley +1 more source
Possibilistic Induction in Decision-Tree Learning [PDF]
, 2002 We propose a generalization of Ockham's razor, a widely applied principle of inductive inference. This generalization intends to capture the aspect of uncertainty involved in inductive reasoning. To this end, Ockham's razor is formalized within the framework of possibility theory: It is not simply used for identifying a single, apparently optimal model,
openaire +2 more sources
Unperceivable Designs of Wearable Electronics
Advanced Materials, EarlyView.Unperceivable wearable technologies seamlessly integrate into everyone's daily life, for healthcare and Internet‐of‐Things applications. By remaining completely unnoticed both visually and tactilely, by the user and others, they ensure medical privacy and allow natural social interactions.
Yijun Liu +2 more
wiley +1 more source
Cost-Sensitive Decision Trees with Completion Time Requirements [PDF]
In many classification tasks, managing costs and completion times are the main concerns. In this paper, we assume that the completion time for classifying an instance is determined by its class label, and that a late penalty cost is incurred if the ...
Hung-Pin KAO, Jen TANG, Kwei TANG
core
, 2020 Decision tree algorithms have been among the most popular algorithms for interpretable (transparent) machine learning since the early 1980's. The problem that has plagued decision tree algorithms since their inception is their lack of optimality, or lack
Hu, Xiyang +2 more
core