Results 51 to 60 of about 87,026 (282)

Formal Verification of Input-Output Mappings of Tree Ensembles

, 2020
Recent advances in machine learning and artificial intelligence are now being considered in safety-critical autonomous systems where software defects may cause severe harm to humans and the environment. Design organizations in these domains are currently
Nadjm-Tehrani, Simin, Törnblom, John
core   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

The Error is the Feature: how to Forecast Lightning using a Model Prediction Error

, 2019
Despite the progress within the last decades, weather forecasting is still a challenging and computationally expensive task. Current satellite-based approaches to predict thunderstorms are usually based on the analysis of the observed brightness ...
Andersson T., Bott Andreas, Ernst Ludwig Planck Max Karl, Lang P, Ruiz Anne, Veillette Mark S., Williams John K., Zach Christopher   +7 more
core   +1 more source

Developing Children's Oral Health Assessment Toolkits Using Machine Learning Algorithm. [PDF]

, 2020
ObjectivesEvaluating children's oral health status and treatment needs is challenging. We aim to build oral health assessment toolkits to predict Children's Oral Health Status Index (COHSI) score and referral for treatment needs (RFTN) of oral health ...
Coulter, ID, Crall, JJ, Hays, RD, Lee, SY, Liu, H, Maida, CA, Marcus, M, Shen, J, Spolsky, VW, Wang, Y, Xiong, D   +10 more
core  

Unique Performance Considerations for Printable Organic Semiconductor and Perovskite Radiation Detectors: Toward Consensus on Best Practice Evaluation

Advanced Functional Materials, EarlyView.
A lack of standard approaches for testing and reporting the performance of metal halide perovskites and organic semiconductor radiation detectors has resulted in inconsistent interpretation of performance parameters, impeding progress in the field. This Perspective recommends key metrics and experimental details, which are suggested for reporting in ...
Jessie A. Posar, Matthew Large, Andrea Ciavatti, Laura Basiricò, Beatrice Fraboni, Paul J. Sellin, Attila J. Mozer, Marco Petasecca, Matthew J. Griffith   +8 more
wiley   +1 more source

A Generalized Linear Model and Machine Learning Approach for Predicting the Frequency and Severity of Cargo Insurance in Thailand’s Border Trade Context

Risks
The study compares model approaches in predictive modeling for claim frequency and severity within the cross-border cargo insurance domain. The aim is to identify the optimal model approach between generalized linear models (GLMs) and advanced machine ...
Praiya Panjee, Sataporn Amornsawadwatana
doaj   +1 more source

Potential of Remote Sensing Images for Soil Moisture Retrieving Using Ensemble Learning Methods in Vegetation-Covered Area

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Soil moisture (SM) plays a critical role in various fields such as agriculture, hydrology, and land-atmosphere interactions. This study aims to evaluate the performance of the categorical boosting algorithm (CatBoost) in comparison to other multiple ...
Ya Gao, Liguo Wang, Geji Zhong, Yitong Wang, Jinghui Yang   +4 more
doaj   +1 more source

Learning Nonlinear Functions Using Regularized Greedy Forest

, 2013
We consider the problem of learning a forest of nonlinear decision rules with general loss functions. The standard methods employ boosted decision trees such as Adaboost for exponential loss and Friedman's gradient boosting for general loss.
Johnson, Rie, Zhang, Tong
core   +2 more sources

Atomic Size Misfit for Electrocatalytic Small Molecule Activation

Advanced Functional Materials, EarlyView.
This review explores the application and mechanisms of atomic size misfit in catalysis for small molecule activation, focusing on how structural defects and electronic properties can effectively lower the energy barriers of chemical bonds in molecules like H2O, CO2, and N2.
Ping Hong, Changfan Xu, Huaping Zhao, Yong Lei   +3 more
wiley   +1 more source

Machine learning regression models for internal shame

Acta Psychologica
This study aims to predict Internal Shame (IS) based on childhood trauma, social emotional competence, cognitive flexibility, distress tolerance and alexithymia in an Iranian sample.
Nataša Kovač, Kruna Ratković, Hojjatollah Farahani, Peter Watson   +3 more
doaj   +1 more source