Results 111 to 120 of about 6,285,017 (364)

IDRandom-Forest: Advanced Random Forest for Real-Time Intrusion Detection

IEEE Access
In the last decade, with the increase in cyberattacks the privacy of network traffic has become a critical issue. Currently, simple network intrusion detection techniques are inefficient in terms of time complexity and are characterized by low detection ...
Muhammad Azhar, Shahida Perveen, Asma Iqbal, Bumshik Lee   +3 more
doaj   +1 more source

Classification tree and random forest model to predict under-five malnutrition in Bangladesh [PDF]

, 2021
Sabbir Ahmed Hemo, Md. Israt Rayhan
openalex   +1 more source

Fluid Biomarkers of Disease Burden and Cognitive Dysfunction in Progressive Supranuclear Palsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Identifying objective biomarkers for progressive supranuclear palsy (PSP) is crucial to improving diagnosis and establishing clinical trial and treatment endpoints. This study evaluated fluid biomarkers in PSP versus controls and their associations with regional 18F‐PI‐2620 tau‐PET, clinical, and cognitive outcomes.
Roxane Dilcher, Charles B. Malpas, Stuart J. McDonald, William T. O’Brien, Craig Despott, Kelly L. Bertram, Matthew P. Pase, Lukas Frontzkowski, Meng Law, Terence J. O’Brien, Lucy Vivash   +10 more
wiley   +1 more source

An Enhanced Proximal Policy Optimization-Based Reinforcement Learning Method with Random Forest for Hyperparameter Optimization [PDF]

, 2022
Zhixin Ma, Shengmin Cui, Inwhee Joe
openalex   +1 more source

Development of a Personalized Visualization and Analysis Tool to Improve Clinical Care in Complex Multisystem Diseases With Application to Scleroderma

Arthritis Care &Research, EarlyView.
Objective In complex diseases, it is challenging to assess a patient's disease state, trajectory, treatment exposures, and risk of multiple outcomes simultaneously, efficiently, and at the point of care. Methods We developed an interactive patient‐level data visualization and analysis tool (VAT) that automates illustration of the trajectory of a ...
Ji Soo Kim, John Scott, Lauren Fisher, Lauren N. Smith, Willie Stewart, Adrianne Woods, Rob Smithwright, Diane Koher, Parastoo Aslanbeik, Aalok B. Shah, Brad Tibbils, Samantha I. Pitts, Ayse P. Gurses, Yushi Yang, Ana‐Maria Orbai, Antony Rosen, Laura K. Hummers, Scott L. Zeger, Ami A. Shah   +18 more
wiley   +1 more source

Effect of Hyperparameter Tuning Using Random Search on Tree-Based Classification Algorithm for Software Defect Prediction

IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
The field of information technology requires software, which has significant issues. Quality and reliability improvement needs damage prediction. Tree-based algorithms like Random Forest, Deep Forest, and Decision Tree offer potential in this domain ...
Muhammad Hevny Rizky, Mohammad Reza Faisal, Irwan Budiman, Dwi Kartini, Friska Abadi   +4 more
doaj   +1 more source

Random forest regression for predicting an anomalous condition on a UR10 cobot end-effector from purposeful failure data

, 2021
Ethan Wescoat, Matthew Krugh, Laine Mears   +2 more
openalex   +1 more source

Economic Burden of Rheumatoid Arthritis in Low‐ and Middle‐Income Countries: Systematic Review and Meta‐Analysis

Arthritis Care &Research, EarlyView.
Objective The aim of this systematic review was to synthesize the economic impact of rheumatoid arthritis (RA) on households, health systems, and society in low‐ and middle‐income countries (LMICs). Methods Electronic databases such as PubMed, Web of Science, and CINAHL were searched using keywords related to RA and cost of illness.
Tadesse Gebrye, Chidozie E. Mbada, Clara T. Fatoye, Faatihah Niyi‐Odumosu, Ushotanefe Useh, Zalmai Hakimi, Francis Fatoye   +6 more
wiley   +1 more source

Oblique random survival forests

The Annals of Applied Statistics, 2019
We introduce and evaluate the oblique random survival forest (ORSF). The ORSF is an ensemble method for right-censored survival data that uses linear combinations of input variables to recursively partition a set of training data. Regularized Cox proportional hazard models are used to identify linear combinations of input variables in each recursive ...
Jaeger, Byron C., Long, D. Leann, Long, Dustin M., Sims, Mario, Szychowski, Jeff M., Min, Yuan-I, Mcclure, Leslie A., Howard, George, Simon, Noah   +8 more
openaire   +3 more sources

Random Prism: An Alternative to Random Forests [PDF]

, 2011
Ensemble learning techniques generate multiple classifiers, so called base classifiers, whose combined classification results are used in order to increase the overall classification accuracy. In most ensemble classifiers the base classifiers are based on the Top Down Induction of Decision Trees (TDIDT) approach.
Stahl, F., Bramer, Max
openaire   +2 more sources