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相关概念视频

Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

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Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
Generalization occurs when a behavior reinforced in one context is performed in similar situations. For instance, a student who studies diligently for calculus and receives excellent grades might apply the same study habits to psychology and history, expecting similar results. Generalization shows how learning in one setting can influence behavior in...
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Survival Tree01:19

Survival Tree

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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...
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Variability: Analysis01:11

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Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
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Prediction Intervals01:03

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The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
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The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
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Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
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预期的变化增加了预测性学习的概括性.

Hadar Ram1, Guy Grinfeld2, Nira Liberman2,3

  • 1Bar-Ilan University, Tel Aviv, Israel. hadar.ram@biu.ac.il.

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概括
此摘要是机器生成的。

当学习者期望未来任务变化更大时,他们会更广泛地概括. 这种"更广泛的网络"方法平衡了学习信息的准确性和适用性.

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科学领域:

  • 认知心理学 认知心理学
  • 学习科学 学习科学
  • 感知 感知 感知 感知

背景情况:

  • 一般化对于将学到的信息应用于新情况至关重要.
  • 了解影响概括广度的因素是优化学习的关键.

研究的目的:

  • 调查预期的变化如何影响感知概括.
  • 探索预期的任务变化和学习范围之间的关系.

主要方法:

  • 在三个实验中利用了预测性学习任务.
  • 通过明确的指令和时间距离操纵预期的变化.
  • 评估了对学习刺激的反应中的概括模式.

主要成果:

  • 当学习者期望学习和概括集之间更高的变化时,学习者更广泛地概括.
  • 明确的指令和增加时间距离应用程序增强了概括.
  • 预计未来应用在更遥远的环境中增加了预期的变化.

结论:

  • 预期的变异性显著影响了概括的广度.
  • 准确性-适用性权衡解释了这一现象:当目标变化更大时,会发生更广泛的概括.
  • 这些发现与构造级理论一致,建议对遥远的未来应用进行抽象分类.