Decision Trees and Random Forests: Nonlinear and Nonparametric Alternatives to Logistic Regression in Biological Data Analysis

IF 21 1区医学 Q1 ONCOLOGY

Journal of Thoracic Oncology Pub Date : 2025-07-01 DOI:10.1016/j.jtho.2025.03.003

Yoshiyasu Takefuji PhD

引用次数: 0

查看原文本刊更多论文

决策树和随机森林：生物数据分析中逻辑回归的非线性和非参数替代方案

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Journal of Thoracic Oncology 医学-呼吸系统

CiteScore

36.00

自引率

3.90%

发文量

1406

审稿时长

13 days

期刊介绍： Journal of Thoracic Oncology (JTO), the official journal of the International Association for the Study of Lung Cancer,is the primary educational and informational publication for topics relevant to the prevention, detection, diagnosis, and treatment of all thoracic malignancies.The readship includes epidemiologists, medical oncologists, radiation oncologists, thoracic surgeons, pulmonologists, radiologists, pathologists, nuclear medicine physicians, and research scientists with a special interest in thoracic oncology.