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相关概念视频

Attribution Theory00:56

Attribution Theory

13.0K
Behavior is a product of both the situation (e.g., cultural influences, social roles, and the presence of bystanders) and of the person (e.g., personality characteristics). Subfields of psychology tend to focus on one influence or behavior over others. Situationism is the view that our behavior and actions are determined by our immediate environment and surroundings. In contrast, dispositionism holds that our behavior is determined by internal factors (Heider, 1958).
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Fundamental Attribution Error01:14

Fundamental Attribution Error

12.9K
According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is...
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Cause and Effect01:53

Cause and Effect

10.9K
While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
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Second Uniqueness Theorem01:16

Second Uniqueness Theorem

1.0K
Consider a region consisting of several individual conductors with a definite charge density in the region between these conductors. The second uniqueness theorem states that if the total charge on each conductor and the charge density in the in-between region are known, then the electric field can be uniquely determined.
In contrast, consider that the electric field is non-unique and apply Gauss's law in divergence form in the region between the conductors and the integral form to the...
1.0K
Criteria for Causality: Bradford Hill Criteria - II01:28

Criteria for Causality: Bradford Hill Criteria - II

321
The Bradford Hill criteria serve as guidelines for establishing causative links in epidemiological research. Beyond Strength, Consistency, Specificity, and Temporality, key criteria also include Biological Gradient, Plausibility, Coherence, Experiment, and Analogy. These principles assist scientists in assessing the likelihood of causation in complex biological contexts. Below is a summary of these concepts:
321
The Representativeness Heuristic02:13

The Representativeness Heuristic

15.8K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
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相关实验视频

Updated: Jul 6, 2025

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
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Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

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对于特征归属的不可能定理.

Blair Bilodeau1, Natasha Jaques2, Pang Wei Koh2

  • 1Department of Statistical Sciences, University of Toronto, Toronto, ON M5G 1Z5, Canada.

Proceedings of the National Academy of Sciences of the United States of America
|January 5, 2024
PubMed
概括
此摘要是机器生成的。

像集成梯度和SHAP这样的特征归属方法可能会在神经网络中失败. 定义特定的最终任务允许更简单的模型评估超过复杂的方法.

关键词:
可以解释的人工智能AI属性属性 属性属性 属性属性 属性属性可以解释的解释性.

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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

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Generating Strictly Controlled Stimuli for Figure Recognition Experiments
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Generating Strictly Controlled Stimuli for Figure Recognition Experiments

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相关实验视频

Last Updated: Jul 6, 2025

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

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科学领域:

  • 人工智能的人工智能
  • 机器学习 机器学习
  • 可解释的人工智能 (XAI)

背景情况:

  • 存在许多可解释性方法,但经验上的失败引起了人们对其实际应用的担忧.
  • 实践者缺乏关于原则性使用和选择特征归因方法的明确指导.

研究的目的:

  • 为适度丰富的模型类展示完整和线性特征归因方法的理论限制.
  • 突出最终任务定义在评估可解释性方法中的重要性.

主要方法:

  • 根据特定假设 (完整性,线性) 进行特征归因方法的理论分析.
  • 跨常见终端任务的调查:局部行为特征,虚假特征识别和算法诉求.
  • 与重复模型评估的基线方法进行比较.

主要成果:

  • 完整和线性特征归属方法在推断模型行为方面不能比随机猜测更好地执行.
  • 这些限制适用于广泛使用的方法,如集成梯度和Shapley添加式解释 (SHAP).
  • 一个简单的重复模型评估策略可以超过复杂的方法,当最终任务是明确的.

结论:

  • 当前的特征归因方法可能无法可靠地提高对复杂模型的理解.
  • 对最终任务的精确定义对于有效的模型解释至关重要.
  • 精确定义的最终任务可以实现更简单,更直接的评估策略,这些策略可能比复杂的特征归因技术更有效.