Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

271
Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
271
Multiple Regression01:25

Multiple Regression

3.7K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.7K
Regression Analysis01:11

Regression Analysis

7.8K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
7.8K
Regression Toward the Mean01:52

Regression Toward the Mean

6.8K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.8K
Truncation in Survival Analysis01:09

Truncation in Survival Analysis

553
Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
553
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

467
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
467

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Anonymised human location data in England for urban mobility research.

Scientific data·2025
Same author

Adaptive law-based feature representation for time series classification.

Scientific reports·2025
Same author

Unified causality analysis based on the degrees of freedom.

Physical review. E·2025
Same author

Dataset on global trade networks of COVID-19 medical products.

Data in brief·2024
Same author

Holistic view of the seascape dynamics and environment impact on macro-scale genetic connectivity of marine plankton populations.

BMC ecology and evolution·2023
Same author

The Debiased Spatial Whittle likelihood.

Journal of the Royal Statistical Society. Series B, Statistical methodology·2023
Same journal

Peripheral B-cell receptor repertoire predicts immune-related adverse events following immune checkpoint inhibitor therapy in advanced renal cell carcinoma.

Scientific reports·2026
Same journal

Effects of black soldier fly (Hermetia illucens L.) larvae zoocompost on the mineral element content of blue honeysuckle berries.

Scientific reports·2026
Same journal

Investigation on absorption refrigeration performance of R1243zf with imidazolium ionic liquid as the working pairs.

Scientific reports·2026
Same journal

DeepTriage-CN: integrating clinical text with vital signs for emergency department admission prediction in an aging population.

Scientific reports·2026
Same journal

Gold nanoparticles as dual-action antiviral agents: disruption of SARS-CoV-2 viral envelopes and RNA integrity.

Scientific reports·2026
Same journal

Comparison of capillary microsampling and venous blood for multi-pathogen serosurveillance.

Scientific reports·2026
查看所有相关文章

相关实验视频

Updated: Jan 10, 2026

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

6.3K

在可解释模型选择中捕捉非线性效应的SplitWise回归.

Marcell T Kurbucz1, Nikolaos Tzivanakis2, Nilufer Sari Aslam2

  • 1Institute for Global Prosperity, The Bartlett, University College London, 9-11 Endsleigh Gardens, London, WC1H 0EH, UK. m.kurbucz@ucl.ac.uk.

Scientific reports
|November 27, 2025
PubMed
概括
此摘要是机器生成的。

SplitWise是一个新的回归框架,它平衡了模型的可解释性与非线性关系. 它适应性地转换预测器,提高准确性,同时保持透明,线性模型.

关键词:
假变量是一个假变量.可以解释的建模.模型选择 模型选择软件 软件 软件 软件 软件一步一步的回归回归.值效应是一种值效应.

更多相关视频

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

8.6K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.7K

相关实验视频

Last Updated: Jan 10, 2026

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

6.3K
Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

8.6K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.7K

科学领域:

  • 统计 统计 统计 统计
  • 机器学习 机器学习
  • 数据科学数据科学数据科学

背景情况:

  • 回归建模经常努力平衡捕捉非线性关系与保持模型可解释性.
  • 经典的线性模型提供透明度,但不能有效地模拟复杂的非线性模式.
  • 现有的可解释的非线性方法可能缺乏灵活性或引入复杂性.

研究的目的:

  • 介绍SplitWise,这是一种新的逐步回归框架,旨在弥合线性可解释性和非线性灵活性之间的差距.
  • 开发一种方法,适应性地将数值预测器转换为二进制特征,只有在有利于模型合适的情况下.
  • 提供一种回归方法,在捕捉基于值的非线性效应的同时,仍然可以解释和验证.

主要方法:

  • SplitWise采用浅层决策树来识别将数值预测器转换为二进制特征的最佳值.
  • 模型合适性是使用Akaike信息标准 (AIC) 或贝叶斯信息标准 (BIC) 来评估的,以指导预测器转换.
  • 该框架将这些二进制特征集成到全球线性方程中,保持整体模型透明度.

主要成果:

  • 在合成数据上,与线性基线相比,SplitWise将中位数根平均平方误差 (RMSE) 降低了7-14%.
  • 变量选择精度得到了改进,马修斯相关系数 (MCC) 达到0.79比LASSO的0.51.
  • 在真实数据集 (葡萄酒质量,体脂) 上,SplitWise 实现了与其他方法相比较少选择预测因素的可比或改进的 RMSE.

结论:

  • SplitWise提供了一个可解释但灵活的回归建模方法,有效地捕获基于值的非线性.
  • 与传统的线性模型和一些先进的方法相比,该框架提高了预测准确性和变量选择.
  • 对于寻求具有增强预测能力的透明模型的研究人员和从业人员来说,SplitWise是一个有价值的工具.