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

Binomial Probability Distribution01:15

Binomial Probability Distribution

10.2K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
10.2K
Classification of Systems-I01:26

Classification of Systems-I

176
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
176
Survival Tree01:19

Survival Tree

61
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
61
Classification of Systems-II01:31

Classification of Systems-II

136
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
136
Associative Learning01:27

Associative Learning

303
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
303
Bias01:22

Bias

3.8K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
3.8K

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

Spatial and temporal modeling of conflict related fatality and public health implications in Nigeria.

Scientific reports·2025
Same author

Global Trends in Risk Factors for Low Back Pain: An Analysis of the Global Burden of Disease Study Data From 1990 to 2021.

Arthritis care & research·2025
Same author

Non-proportional hazards model with a PVF frailty term: application with a melanoma dataset.

Journal of applied statistics·2025
Same author

Graviceptive neglect induced by HD-tDCS of the right or left temporoparietal junction: A within-person randomized trial in healthy adults.

Annals of physical and rehabilitation medicine·2024
Same author

Author Correction: Reducing delivery insurance costs through risk score model for food delivery company.

Scientific reports·2024
Same author

Reducing delivery insurance costs through risk score model for food delivery company.

Scientific reports·2024
Same journal

Modeling and analysis of forward and inverse kinematics for a flexible Stewart platform.

PloS one·2026
Same journal

Barriers and facilitators to healthcare utilization amongst people living with sickle cell disease in the United States: A scoping review.

PloS one·2026
Same journal

Enhancing data completeness in time series: Imputation strategies for missing data using significant periodically correlated components.

PloS one·2026
Same journal

Key targets and mechanisms by which gut microbiota-derived metabolites regulate Alzheimer's disease through the immune - inflammatory pathway: Based on network pharmacology and molecular docking.

PloS one·2026
Same journal

Grid-tied Transformer-less Boost Switched Capacitor Topology (TLBSCT) for PV applications.

PloS one·2026
Same journal

The load-velocity profiles and exercise-specific velocity zones for seven commonly used weightlifting exercises.

PloS one·2026
查看所有相关文章

相关实验视频

Updated: Jun 10, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K

修复不平衡的二进制分类:一个不对称的贝叶斯式学习方法.

Letícia F M Reis1, Diego C Nascimento2, Paulo H Ferreira3

  • 1Institute of Mathematics and Computer Sciences, University of São Paulo, São Carlos, São Paulo, Brazil.

PloS one
|October 16, 2024
PubMed
概括
此摘要是机器生成的。

新的不对称罗马克斯分布模型改善了对不平衡数据的二进制分类. 这些贝叶斯函数在现实应用中优于传统方法,如物流回归.

更多相关视频

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.5K
Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates
08:56

Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates

Published on: January 13, 2023

2.1K

相关实验视频

Last Updated: Jun 10, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.5K
Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates
08:56

Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates

Published on: January 13, 2023

2.1K

科学领域:

  • 统计 统计 统计 统计
  • 机器学习 机器学习
  • 计算统计学 计算统计学

背景情况:

  • 标准的二进制分类模型假定数据是平衡的,这可能导致不平衡数据集的性能差和偏差.
  • 传统的对称链接函数 (例如,logit,probit) 可能无法有效处理具有偏斜数据分布的分类任务.

研究的目的:

  • 介绍基于罗马克斯分布及其变体的二进制回归的新型不对称链接函数.
  • 评估这些新功能在解决分类中的数据不平衡挑战方面的表现.

主要方法:

  • 开发了新的贝叶斯不对称分类函数,使用洛马克斯分布变量 (权力,反向).
  • 在R工作流中使用Stan实现了这些函数,用于贝叶斯推理.
  • 使用现实世界的不平衡数据集,将拟议的模型与经典对称链接函数进行了比较.

主要成果:

  • 拟议的非对称的罗马克斯函数在二进制分类任务中表现出优于传统链接函数的性能.
  • 具体来说,反向功率双 Lomax (RPDLomax) 模型有效地区分了不平衡数据中的失败和成功概率.
  • 与物流回归 (36.0%的失败,39.5%的成功) 不同的是,RPDLomomax的失败概率较低 (21.4%),成功概率较高 (63.7%).

结论:

  • 拟议的非对称的罗马克斯方法为二进制数据分类提供了具有竞争力和有效的替代方案,特别是在数据集不平衡的情况下.
  • 这些新型函数与标准后勤回归相比,可以更好地区分类别.
  • 在R中贝叶斯的实现方便了实际应用和进一步研究非对称二进制回归.