Results 31 to 40 of about 723,870 (293)
IEEE Access, 2021 This paper presents the synthesis of multiband frequency selective surfaces (FSSs) using supervised machine learning (ML) with the decision tree (DT) algorithm.
Leidiane C. M. M. Fontoura +4 more
doaj +1 more source
Efficient algorithms for decision tree cross-validation
, 2001 Cross-validation is a useful and generally applicable technique often employed in machine learning, including decision tree induction. An important disadvantage of straightforward implementation of the technique is its computational overhead.
Blockeel, Hendrik, Struyf, Jan
core +4 more sources
Machine Learning in Injection Molding: An Industry 4.0 Method of Quality Prediction
Sensors, 2022 One of the essential requirements of injection molding is to ensure the stable quality of the parts produced. However, numerous processing conditions, which are often interrelated in quite a complex way, make this challenging.
Richárd Dominik Párizs +3 more
doaj +1 more source
Anthropometric determinants of change of direction speed in youth soccer players: A cross-sectional study using decision tree regression and machine learning approach [PDF]
Medicine (Baltimore)Fray A +6 more
europepmc +2 more sources
Complexity, 2020 Software defects prediction at the initial period of the software development life cycle remains a critical and important assignment. Defect prediction and correctness leads to the assurance of the quality of software systems and has remained integral to
Rashid Naseem +6 more
doaj +1 more source
Generating Buy/Sell Signals for an Equity Share Using Machine Learning [PDF]
Eurasian Journal of Business and Economics, 2018 This study proposes a novel model for predicting 5 days’ ahead share price direction of GARAN (Garanti Bankasi A.Ş.), an equity share that is the top traded stock in BIST100, Istanbul Stock Exchange -Turkey.
Bugra ERKARTA, Linet OZDAMAR
doaj +1 more source
Molecular Oncology, EarlyView.This study investigates gene expression differences between two major pediatric acute lymphoblastic leukemia (ALL) subtypes, B‐cell precursor ALL, and T‐cell ALL, using a data‐driven approach consisting of biostatistics and machine learning methods. Following analysis of a discovery dataset, we find a set of 14 expression markers differentiating the ...
Mona Nourbakhsh +8 more
wiley +1 more source
An application of decision trees method for fault diagnosis of induction motors [PDF]
, 2006 Decision tree is one of the most effective and widely used methods for building classification model. Researchers from various disciplines such as statistics, machine learning, pattern recognition, and data mining have considered the decision tree ...
Oh, Myung-Suck +2 more
core
Investigating Evaluation Measures in Ant Colony Algorithms for Learning Decision Tree Classifiers [PDF]
, 2015 Ant-Tree-Miner is a decision tree induction algorithm that is based on the Ant Colony Optimization (ACO) meta- heuristic. Ant-Tree-Miner-M is a recently introduced extension of Ant-Tree-Miner that learns multi-tree classification models.
Abdelbar, Ashraf M. +2 more
core +1 more source
Molecular Oncology, EarlyView.This study presents a novel AI‐based diagnostic approach—comprehensive serum glycopeptide spectra analysis (CSGSA)—that integrates tumor markers and enriched glycopeptides from serum. Using a neural network model, this method accurately distinguishes liver and pancreatic cancers from healthy individuals.
Motoyuki Kohjima +6 more
wiley +1 more source