Unverified50% confidenceOpinionExact time
Divination systems and machine learning share a philosophical resonance: both rely on feature selection and face the risk of overfitting, but machine learning has explicit validation mechanisms while ancient divination mainly relied on confirmation bias to maintain credibility.
1
Sources
50%
Confidence
Long-term
Relevance
8/13/2026
First Seen
Sources
波斯《蛇卜书》：古代占卜古籍如何在数字时代重获新生
Related Claims
UnverifiedWhen getting started with machine learning, one should adopt a "top-down" learning path of intuition first and mathematics second, rather than systematically completing linear algebra and probability theory first.70% similarUnverifiedFor machine learning, what is needed is conceptual understanding and geometric intuition, not proficiency in manual computation.70% similarUnverified统计学基础应先于机器学习学习，因为数学直觉是读懂模型行为和排查异常结果的底层能力69% similarUnverified多智能体系统的每一步决策都有明确的推理链路，与纯黑箱的机器学习模型不同，具有可解释性68% similarUnverifiedMachine learning engineering, especially in the traditional statistical methods direction, emphasizes the ability to model under uncertainty, requiring an understanding of data distributions, bias-variance trade-offs, feature engineering, and model evaluation67% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/740618API
curl https://kongchang.com/api/v1/knowledge/claims/740618MCP
get_claim(id=740618)