Results 101 to 110 of about 6,098 (213)

Impact of Data Balancing and Feature Engineering on Accident Severity Models

Promet (Zagreb)
This study investigates the impacts of feature engineering techniques, including Clustering, Target Encoding and Anomaly Detection, in conjunction with data balancing methods, on the efficacy of machine learning models for predicting road accident ...
Fayez ALANAZI, Aminu SULEIMAN
doaj   +1 more source

AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML

CoRR
Automated machine learning (AutoML) accelerates AI development by automating tasks in the development pipeline, such as optimal model search and hyperparameter tuning. Existing AutoML systems often require technical expertise to set up complex tools, which is in general time-consuming and requires a large amount of human effort. Therefore, recent works
Patara Trirat, Wonyong Jeong, Sung Ju Hwang   +2 more
openaire   +4 more sources

HIRU AutoML Tool

<p>The HIRU AutoML Tool is a program used to investigate how various combinations of preprocessing steps affect the performance of models trained using Microsoft's AutoML framework.</p ...
Parrish, Rick
core   +1 more source

AutoML Two-Sample Test [PDF]

, 2023
Two-sample tests are important in statistics and machine learning, both as tools for scientific discovery as well as to detect distribution shifts. This led to the development of many sophisticated test procedures going beyond the standard supervised ...
Buchholz, Simon, Muandet, Krikamol, Stimper, Vincent, Schölkopf, Bernhard, Kübler, Jonas M.   +4 more
core  

Towards Human Centered AutoML

CoRR, 2019
Building models from data is an integral part of the majority of data science workflows. While data scientists are often forced to spend the majority of the time available for a given project on data cleaning and exploratory analysis, the time available to practitioners to build actual models from data is often rather short due to time constraints for ...
Florian Pfisterer, Janek Thomas, Bernd Bischl   +2 more
openaire   +2 more sources

Net-Net AutoML of Ecosytems

, 2018
AutoML prediction of ANN topologies able to predict complex ecological networks using shannon information ...
Cristian Robert Munteanu (560454), Humbert Gonzalez-Diaz (5192699)   +1 more
core   +1 more source

Understanding the Role of Diversity in Ensemble-Based AutoML Methods for Classification Tasks

IEEE Access
Ensemble-based Automated Machine Learning (AutoML) methods have gained prominence for their ability to combine diverse machine learning models, achieving superior generalization performance.
Salomey Osei, Andres R. Masegosa, Antonio D. Masegosa   +2 more
doaj   +1 more source

Early detection of broccoli drought acclimation/stress in agricultural environments utilizing proximal hyperspectral imaging and AutoML

Smart Agricultural Technology
Absract: The contemporary field of artificial intelligence has witnessed the emergence of Automated Machine Learning (AutoML) as a noteworthy advancement, promising the delivery of high-performance end-to-end machine learning pipelines with minimal user ...
Ioannis Malounas, Georgios Paliouras, Dimosthenis Nikolopoulos, Georgios Liakopoulos, Panagiota Bresta, Paraskevi Londra, Anastasios Katsileros, Spyros Fountas   +7 more
doaj   +1 more source

On using AutoML to Predict Clinical Outcomes

, 2020
AutoML allows users to create high-quality machine learning models to solve real-world problems without much coding. Recently, Automl has been used in machine learning competitions such as Kaggle and showed excellent performance.
Wendy Wong
core   +1 more source

Development and validation of an automated machine learning model for the multi-class classification of diabetic retinopathy, central retinal vein occlusion and branch retinal vein occlusion based on color fundus photographs

JFO Open Ophthalmology
Introduction: Automated machine learning (AutoML) is a novel artificial intelligence (AI) strategy that enables clinicians without coding experience to develop their own AI models.
Carolyn Yu Tung Wong, Timing Liu, Tin Lik Wong, Justin Man Kit Tong, Henry Hing Wai Lau, Pearse Andrew Keane   +5 more
doaj   +1 more source