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相关概念视频

Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

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Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
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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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End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

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A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
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Self-Evaluation Maintenance Model01:29

Self-Evaluation Maintenance Model

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The Self-Evaluation Maintenance (SEM) model offers a psychological framework to understand how individuals’ self-esteem is influenced by the achievements of others, particularly those with whom they share close personal bonds. The SEM model operates when personal rather than social identity guides individuals. Central to this model is the notion that individuals have an inherent desire to preserve a favorable self-image, which is continuously shaped by interpersonal comparisons and...
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Decision Making: P-value Method01:09

Decision Making: P-value Method

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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
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Prediction Intervals01:03

Prediction Intervals

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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.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
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走向更现实的职业道路预测:评估和方法.

Elena Senger1,2, Yuri Campbell2, Rob van der Goot3

  • 1MaiNLP, Center for Information and Language Processing, LMU Munich, Munich, Germany.

Frontiers in big data
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概括

这项研究比较了职业道路预测模型,包括大型语言模型 (LLM),发现先进的模型和微调可以提高准确性. 洞察力指导现实世界的职业预测系统部署.

关键词:
法学士 (LLM) 是一个专业.职业路径预测 职业路径预测劳动力市场的劳动力市场.推是指一个建议.综合数据 综合数据

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科学领域:

  • 计算机科学 计算机科学
  • 数据科学数据科学数据科学
  • 人工智能的人工智能

背景情况:

  • 职业路径预测 (CPP) 对职业咨询和劳动力规划至关重要.
  • 挑战包括数据变化,自由文本简历和有限的数据集.
  • 现有的CPP模型需要全面评估.

研究的目的:

  • 进行各种CPP模型的比较评估.
  • 为LLMs提出新的模型变体和标准化的方法.
  • 调查数据类型,合成数据和微调对CPP性能的影响.

主要方法:

  • 线性投影,MLP,LSTM和LLM的比较分析.
  • 在不同的输入设置 (标题,描述,自由文本) 中进行评估.
  • 研究合成数据和微调策略.

主要成果:

  • 建立了CPP模型的新性能基准.
  • 揭示了不同建模策略和输入类型之间的权衡.
  • 证明了新的MLP扩展和标准化的LLM方法的有效性.

结论:

  • 大型语言模型显示了职业路径预测的前景.
  • 微调和合成数据可以增强模型概括.
  • 结果为部署有效的CPP系统提供了实际见解.