Search Results - "regression algorithms"

PREDICTIVE MODELING OF ROBBERIES IN CAMPO GRANDE (MS) USING SUPERVISED REGRESSION ALGORITHMS

Authors: Wesley Fabricio Souza Silva Jamil Roberto Dagher Neto

Source: Revista Científica da Polícia Militar de Mato Grosso do Sul - RevPMMS. 2:205-221

Comparison of Linear Regression, Decision Tree Regression, and Random Forest Regression Algorithms in Predicting Baldness Risk

Authors: Sebastianus Adi Santoso Mola Alfonsus Maria De Liguori Goru Christian Jaquelino Lamapaha et al.

Source: MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology). 17:63-66

Evaluating the effectiveness of regression algorithms in predicting cancer progression

Authors: Sudhanshu Maurya Deepak Suresh Asudani Jaishree Jain et al.

Source: IET Conference Proceedings. 2025:1367-1373

A Comprehensive Analysis of Regression Algorithms and Visualizations for Optimizing BigMart Sales Prediction

Authors: Amulya Namana D B AjithKumar Kamalakar Shetty Amrutha V Bhat et al.

Source: 2025 5th International Conference on Soft Computing for Security Applications (ICSCSA). :879-882

Comparative Evaluation of Nonlinear Regression Algorithms for Pre-Silicon Verification Methods

Authors: Alecsandra Rusu Emilian David Marina Țopa et al.

Source: 2025 International Symposium on Signals, Circuits and Systems (ISSCS). :1-4

Comparison of SVM, Naïve Bayes, and Logistic Regression Algorithms for Sentiment Analysis of Fraud and Bots in Purcashing Concert Ticket

Authors: Vania Agresia Ryan Randy Suryono

Source: INOVTEK Polbeng - Seri Informatika. 10:591-602

Public Sentiment Analysis on the Boycott Israel Movement on Platform X Using Random Forest and Logistic Regression Algorithms

Authors: Rachmayanti Tri Agustin Yana Cahyana Kiki Ahmad Baihaqi et al.

Source: Journal of Applied Informatics and Computing, Vol 9, Iss 3, Pp 938-945 (2025)

Subject Terms: logistic regression, sentiment analysis, social media, Electronic computers. Computer science, boycott, QA75.5-76.95, random forest

Access URL: https://doaj.org/article/a3c9aab39cab4947aa2146817c3d852c

Comparison of Xgboost, Random Forest and Logistic Regression Algorithms in Stroke Disease Classification

Authors: Lia Relita Sitompul Adli Abdillah Nababan Mey Lestari Manihuruk et al.

Source: Sinkron. 9:957-968

Air Quality Prediction and Prevention Recommendations based on Regression Algorithms

Authors: Ruiying Xiong

Source: 2025 International Conference on Intelligent Computing and Knowledge Extraction (ICICKE). :1-6

Calories Burnt Prediction Using ANN and XGBoost Regression Algorithms from Physical Activities

Authors: Savarapu Chandra Shekar Dokala Vardhini Sri Gowrineni Kyathi Chandana et al.

Source: 2025 6th International Conference for Emerging Technology (INCET). :1-5

Data-Driven Optimization of Dynamic Properties in Additively Manufactured Parts Using Linear Regression Algorithms

Authors: Can Barış Toprak Can Ulas Dogruer

Source: 2025 The 16th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT). :226-232

ANALYSIS OF MULTIPLE REGRESSION ALGORITHMS TO PREDICT THE VEHICLE RESALE VALUE

Authors: Shubham Singh Durgesh Sharma Sanidhya . et al.

Source: INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING AND TECHNOLOGY. 16:443-451

Comprehensive Evaluation of Regression Algorithms for Power Grid Datasets: Effectiveness and Robustness Analysis

Authors: Xuxian Wang Bao Wen Jiahui Zhu et al.

Source: 2025 8th International Conference on Energy, Electrical and Power Engineering (CEEPE). :580-585

Perbandingan Performansi Algoritma Multiple Linear Regression dan Multi Layer Perceptron Neural Network dalam Memprediksi Penjualan Obat: Comparison of the Performance of Multiple Linear Regression Algorithms and Multi Layer Perceptron Neural Networks in Predicting Drug Sales

Authors: Danang Arifuddin Kusrini Kusrini Kusnawi Kusnawi

Source: MALCOM: Indonesian Journal of Machine Learning and Computer Science. 5:722-737

Comparison of Naïve Bayes, Random Forest, and Logistic Regression Algorithms for Sentiment Analysis Online Gambling

Authors: null Dwi Nanda Agustia null Ryan Randy Suryono

Source: INOVTEK Polbeng - Seri Informatika. 10:284-295

Leveraging Machine Learning Regression Algorithms to Predict Mechanical Properties of Evaporitic Rocks From Their Physical Attributes

Authors: Ayham Zaitouny Hasan Arman Anusuya Krishnan et al.

Source: IEEE Access, Vol 13, Pp 123097-123109 (2025)

Subject Terms: machine learning, geotechnical engineering, nonlinear correlations, ensemble learning, Electrical engineering. Electronics. Nuclear engineering, mechanical properties, Evaporitic rocks, TK1-9971

Access URL: https://doaj.org/article/e31d533627dc4a3f80ff7462f4ee6a97

Optimization and artificial intelligence: An in-depth analysis of multi-objective optimization, sampling methods, and regression algorithms applied to structural design

Authors: Guilherme Ferreira Gomes Kouider Bendine Joao Luiz Junho Pereira

Source: Mechanics Based Design of Structures and Machines. 53:5822-5849

A Comparative Analysis of Regression Algorithms in Lung Cancer Prediction

Authors: Prakash Kumar Jha Avni Garg Ramachandran T et al.

Source: 2025 International Conference on Automation and Computation (AUTOCOM). :905-910

Optimized Fused Regression Model for Regression Algorithms

Authors: null Swati Gupta

Source: Journal of Information Systems Engineering and Management. 10:685-697

Detecting soil mixing, grain size distribution, and clogging potential of tunnel excavation face by classification-regression algorithms using EPBM operational data

Authors: Sharmin Sarna Marte Gutierrez

Source: Underground Space, Vol 20, Iss, Pp 311-354 (2025)

Subject Terms: Clogging, Machine learning, 0211 other engineering and technologies, TA703-712, EPBM tunneling, Mixed soil, Engineering geology. Rock mechanics. Soil mechanics. Underground construction, 02 engineering and technology, Grain size, Stochastic hill climbing-adaptive steps

Access URL: https://doaj.org/article/ab2fa76c873d4f8fbb997be053468df9