Search Results - CART and Random tree Algorithm

Final weight prediction from body measurements in Kıvırcık lambs using data mining algorithms.

Authors: Şengül, Ömer Çelik, Şenol

Source: Archives Animal Breeding / Archiv Tierzucht. 2025, Vol. 68 Issue 2, p325-337. 13p.

Subjects: Standard deviations, Regression trees, Random forest algorithms, Data mining, Lambs

Comparison of Tree‐Based Machine Learning Algorithms for Classification of Livestock Breeds Based On Post‐Thaw Spermatological Parameters.

Authors: Özen, Doğukan Özen, Hülya Gül, Elif Bersu et al.

Source: Veterinary Medicine & Science. Sep2025, Vol. 11 Issue 5, p1-10. 10p.

Subjects: Livestock breeds, Machine learning, Semen analysis, CART algorithms, Classification, Cattle breeds

Predicting Weaning Weight of Romanov Lambs From Biometric Measurements Before Weaning Age Using Machine Learning Algorithms.

Authors: Eroğlu, Mehmet Turgut, Ali Osman Küçük, Mürsel et al.

Source: Veterinary Medicine & Science. Jul2025, Vol. 11 Issue 4, p1-8. 8p.

Subjects: Machine learning, Animal breeding, Animal health, Artificial selection of animals, Random forest algorithms

Predicting body weight in Ross 308 broiler chickens using a data mining algorithm approach.

Authors: Bila, L.¹ bilalubabalo94@gmail.com

Source: South African Journal of Animal Science. 2025, Vol. 55 Issue 6, p291-303. 13p.

Subjects: Broiler chickens, Data mining, Prediction models, Poultry as food, Predictive validity, Decision trees, Weighing instruments, Morphology

Leveraging mixed-effects regression trees for the analysis of high-dimensional longitudinal data to identify the low and high-risk subgroups: simulation study with application to genetic study.

Authors: Jahangiri, Mina Kazemnejad, Anoshirvan Goldfeld, Keith S. et al.

Source: BioData Mining; 3/19/2025, Vol. 18 Issue 1, p1-18, 18p

Subject Terms: GENETIC profile, SINGLE nucleotide polymorphisms, AUTOREGRESSIVE models, INDEPENDENT variables, BODY mass index, REGRESSION trees

Using biometric analysis to estimate body weight in Creole goats.

Authors: Trillo-Zárate, Fritz Paredes-Chocce, Miguel Enrique Salinas, Jorge et al.

Source: Open Veterinary Journal. 2025, Vol. 15 Issue 9, p4496-4504. 9p.

Subjects: Body weight, Prediction models, Biometry, Livestock farms, Data mining, Goats, Support vector machines, Random forest algorithms

Geographic Terms: Peru (Viceroyalty)

Estimation of Marketing Live Weight of Lambs by Different Machine Learning Algorithms.

Authors: Karakus, F.¹ fkarakus@yyu.edu.tr

Source: Indian Journal of Animal Research. Jan2025, Vol. 59 Issue 1, p156-162. 7p.

Subjects: Artificial neural networks, Machine learning, Standard deviations, Radial basis functions, Support vector machines

Comparison of machine learning algorithms and multiple linear regression for live weight estimation of Akkaraman lambs.

Authors: Kozaklı, Özge Ceyhan, Ayhan Noyan, Mevlüt

Source: Tropical Animal Health & Production. Sep2024, Vol. 56 Issue 7, p1-10. 10p.

Shrinkage and tree-based regression methods for the prediction of the live weight of Akkaraman sheep using morphological traits.

Authors: Ozen, Hulya Ozen, Dogukan Kocakaya, Afsin et al.

Source: Tropical Animal Health & Production. Nov2024, Vol. 56 Issue 8, p1-10. 10p.

Comparison of some non-linear functions to describe the growth for Linda geese with CART and XGBoost algorithms.

Authors: Tirink, Cem Önder, Hasan Yurtseven, Sabri et al.

Source: Czech Journal of Animal Science. 2022, Vol. 67 Issue 11, p454-464. 11p.

Subjects: CART algorithms, Nonlinear functions, Geese, Standard deviations, Breeding, Akaike information criterion

Comparison of Bayesian Regularized Neural Network, Random Forest Regression, Support Vector Regression and Multivariate Adaptive Regression Splines Algorithms to Predict Body Weight from Biometrical Measurements in Thalli Sheep.

Alternate Title: Thalli Koyunlarında Biyometrik Ölçümlerden Vücut Ağırlığı Tahmini İçin Bayesian Regularized Neural Network, Random Forest Regresyon, Support Vector Regresyon ve Çok Değişkenli Regresyon Uzanımları Algoritmalarının Karşılaştırılması

Authors: TIRINK, Cem¹ cem.tirink@gmail.com

Source: Kafkas Üniversitesi Veteriner Fakültesi Dergisi. May/Jun2022, Vol. 28 Issue 3, p411-419. 9p.

Subjects: Random forest algorithms, Body weight, Splines, Sheep breeds, Sheep, Ear, Artificial neural networks

Using a Decision Tree Algorithm Predictive Model for Sperm Count Assessment and Risk Factors in Health Screening Population.

Authors: Huang, Hung-Hsiang Lu, Chi-Jie Jhou, Mao-Jhen et al.

Source: Risk Management & Healthcare Policy; Nov2023, Vol. 16, p2469-2478, 10p

Subject Terms: HEALTH risk assessment, DECISION trees, SPERM count, INFERTILITY, CART algorithms, MACHINE learning

Analyzing Time Complexity in Machine Learning Algorithms for Big Data: A Study on the Performance of Decision Trees, Neural Networks, and SVMs

Authors: Pichaimani, Thirunavukkarasu Ratnala, Anil Kumar Parida, Priya Ranjan

Source: Journal of Science & Technology; Vol. 5 No. 1 (2024): Journal of Science & Technology; 164-205; 2582-6921

Index Terms: time complexity, decision trees, info:eu-repo/semantics/article, info:eu-repo/semantics/publishedVersion, Peer Reviewed Article

URL: https://thesciencebrigade.com/jst/article/view/454
https://thesciencebrigade.com/jst/article/view/454/426
https://thesciencebrigade.com/jst/article/view/454/426

Diagnosis of lameness via data mining algorithm by using thermal camera and image processing method in Brown Swiss cows.

Authors: Coşkun, Gizem Şahin, Özcan Delialioğlu, Rabia Albayrak et al.

Source: Tropical Animal Health & Production. Feb2023, Vol. 55 Issue 1, p1-8. 8p.

Development of a Machine Learning Algorithm to Correlate Lumbar Disc Height on X-rays with Disc Bulging or Herniation.

Authors: Lin, Pao-Chun Chang, Wei-Shan Hsiao, Kai-Yuan et al.

Source: Diagnostics (2075-4418); Jan2024, Vol. 14 Issue 2, p134, 14p

Subject Terms: MACHINE learning, SPINAL surgery, LUMBAR vertebrae diseases, HERNIA, X-rays, DECISION trees, RANDOM forest algorithms

A Bias Correction Algorithm for the Gini Variable Importance Measure in Classification Trees

Authors: Sandri, Marco Zuccolotto, Paola

Source: Journal of Computational and Graphical Statistics, 2008 Sep 01. 17(3), 611-628.

Access URL: https://www.jstor.org/stable/27594328

Regression Tree Analysis Using TARGET

Authors: Fan, Guangzhe Gray, J. Brian

Source: Journal of Computational and Graphical Statistics, 2005 Mar 01. 14(1), 206-218.

Access URL: https://www.jstor.org/stable/27594105

Nonparametric Variable Selection: The EARTH Algorithm

Authors: Doksum, Kjell Tang, Shijie Tsui, Kam-Wah

Source: Journal of the American Statistical Association, 2008 Dec 01. 103(484), 1609-1620.

Access URL: https://www.jstor.org/stable/27640208

Investigation of Egg Quality Characteristics Affecting Egg Weight of Lohmann Brown Hen with Data Mining Methods.

Authors: Tyasi, Thobela Louis Celik, Senol

Source: Poultry Science Journal. Mar2024, Vol. 12 Issue 1, p107-117. 11p.

Exploratory Data Mining Techniques (Decision Tree Models) for Examining the Impact of Internet-Based Cognitive Behavioral Therapy for Tinnitus: Machine Learning Approach

Authors: Rodrigo, Hansapani Beukes, Eldré W Andersson, Gerhard, Fil dr, Med dr et al.

Source: Journal of Medical Internet Research. 23(11)

Subject Terms: tinnitus, internet interventions, digital therapeutics, cognitive behavioral therapy, artificial intelligence, machine learning, data mining, decision tree, random forest

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-181218
https://doi.org/10.2196/28999