Results 121 to 130 of about 40,856 (264)

Optimizing Random Forest Parameters with Hyperparameter Tuning for Classifying School-Age KIP Eligibility in West Java

Jambura Journal of Mathematics
Random Forest is an ensemble learning algorithm that combines multiple decision trees to generate a more stable and accurate classification model. This study aims to optimize Random Forest parameters for classifying school-age students' eligibility for ...
Silfiana Lis Setyowati, Asyifah Qalbi, Rafika Aristawidya, Bagus Sartono, Aulia Rizki Firdawanti   +4 more
doaj   +1 more source

Antithrombin: Deficiency, Diversity, and the Future of Diagnostics

Mass Spectrometry Reviews, EarlyView.
ABSTRACT Our healthcare system provides reactive sick‐care, treating patients after symptoms have appeared by prescription of generic and often suboptimal therapy. This strategy brings along high costs and high pressure which is not sustainable.
Mirjam Kruijt, Christa M. Cobbaert, L. Renee Ruhaak   +2 more
wiley   +1 more source

Enhancing Accuracy by Using Boosting and Stacking Techniques on the Random Forest Algorithm on Data from Social Media X

Ilkom Jurnal Ilmiah
Online loans (commonly referred to as Pinjol) have become a widespread phenomenon in Indonesia, both in legal and illegal forms. It is undeniable that this is in line with the rapid development and innovation of technology.
Teri Ade Putra, Vicky Ariandi, Sarjon Defit   +2 more
doaj   +1 more source

Who is local and what do they know? Braiding knowledges within carnivore management in Europe

People and Nature, EarlyView.
Abstract Growing recognition of Indigenous Peoples and traditional local communities as stewards of biodiversity has brought to the fore the issues of knowledge and value pluralism in conservation policy and practice. Given their basis in practical and multi‐generational experience, Indigenous and local knowledges are highly relevant to managing human ...
Hanna Pettersson, Lou Lécuyer, Juliette Young, Lindsay Stringer, Simon Calla, Erika Juhász, Zsolt Molnár   +6 more
wiley   +1 more source

Handling imbalanced samples in landslide susceptibility evaluation

Shuiwen dizhi gongcheng dizhi
In landslide susceptibility assessment, different approaches to handling sample imbalance can introduce significant uncertainty in evaluation outcomes.
You TIAN, Bo GAO, Hong YIN, Yuanling LI, Jiajia ZHANG, Long CHEN, Hongliang LI   +6 more
doaj   +1 more source

Seasonality of fruiting phenology, hunting behaviour and taste preferences in Madagascar's Makira Protected Area

People and Nature, EarlyView.
Abstract For many people around the world, especially in Indigenous communities, seasonal changes affect the availability and desirability of different types of food. Assessing the relationship between seasonality, sociocultural preferences and hunting patterns is vital for understanding how these populations harness seasonal food production dynamics ...
Emerson Arehart, Sappho Z. Gilbert, B. J. Rodolph Rasolofoniaina, Evelin J. G. Anjaranirina, Laurent Ravaoliny, Hervet J. Randriamady, Christopher D. Golden   +6 more
wiley   +1 more source

Cassava Diseases Classification using EfficientNet Model with Imbalance Data Handling

JOIN: Jurnal Online Informatika
This research highlights the urgent need for classifying cassava diseases into five classes, such as Cassava Bacterial Blight (CBB), Cassava Brown Streak Disease (CBSD), Cassava Green Mottle (CGM), and Cassava Mosaic Disease (CMD), and Healthy. The study
Stephany Octaviani Ngesthi, Lili Ayu Wulandhari   +1 more
doaj   +1 more source

Biodiversity science is improved when silent herbaria speak

PLANTS, PEOPLE, PLANET, EarlyView.
Herbaria in the Global South are critical yet underutilized resources for biodiversity science and often absent from international databases and research networks. We highlight the phenomenon of “silent herbaria” using Nigeria as a case study and quantify how these collections fill important gaps in global biodiversity knowledge.
Daniel A. Zhigila, Ryan J. Schmidt‐Knapik, Barbara M. Thiers, Suleiman D. Abdul, Salihu Abdullahi, Abdullahi A. AbdulRahaman, Emmanuel I. Aigbokhan, Gabriel A. Ajibade, Linus B. Ajikah, Ferdinand A. Akomaye, Abiodun E. Ayodele, Joseph J. Azila, Aliyu Babale, Abubakar Bello, Deborah M. Chukwuma, Emmanuel C. Chukwuma, Abubakar M. Dadile, Chimezie Ekeke, Iroka C. Finian, Abayomi E. Folorunso, Akanni T. Gbenga, Mohammed R. Haruna, Jemilat A. Ibrahim, Opeyemi S. Kolawole, Abubakar M. Liman, Ferdinand N. Mbagwu, Sunusi Namadi, Victor S. Njom, George I. Nodza, Felix I. Nwafor, Onyebuchi E. Nwankwo, Caleb D. Obadiah, Bamigboye S. Oloruntoba, Fatima B. J. Sawa, Yohanna C. Tumba, Musa Umar, Elizabeth N. Usen, Maryam M. Wabili, Charles C. Davis   +38 more
wiley   +1 more source

CS-SMOTE: An Improved Oversampling Method Combining SMOTE Method and Symmetrical Cube Scoring Mechanism

Symmetry
For classification problems, an imbalanced dataset can seriously reduce the learning efficiency in machine learning. In order to solve this problem, many scholars have proposed a series of methods mainly from the data and algorithm levels. At the data level, SMOTE is one of the most effective methods; it creates new minority samples through linearly ...
Shihao Song, Sibo Yang, Mengqi Sun
openaire   +1 more source

Machine learning‐based predictive models versus traditional risk scores in hemodialysis patients with comorbid urolithiasis

Precision Medical Sciences, EarlyView.
Machine learning‐based predictive models outperform traditional risk scores in hemodialysis patients with comorbid urolithiasis by capturing nonlinear, dialysis‐specific interactions. These approaches enable more accurate prediction of stone recurrence, sepsis, hospitalization, and mortality, supporting personalized risk stratification and precision ...
Dipal Chaulagain, Muhammad Riaz, Mirza Muhammad Hadeed Khawar, Jawad Hameed, Malik Sohail Riaz   +4 more
wiley   +1 more source