· Xiaojing Yang · Statistics
Bootstrap Resampling for Model Evaluation
Bootstrap resampling estimates uncertainty by repeatedly reusing the observed test set.
Blog
Foundations and research notes on mathematics, statistics, machine learning, NLP, LLMs, model evaluation, and applied AI systems.
- · Xiaojing Yang · Statistics
Confidence Intervals: Why One Score Is Not Enough
A model score without uncertainty is easy to read but easy to overtrust.
- · Xiaojing Yang · Statistics
Correlation vs. Causation in AI Research
Correlation is useful evidence, but causal claims require stronger design and stronger assumptions.
- · Xiaojing Yang · Machine Learning
Cross-Validation for Model Evaluation
Why one split is fragile, how K-fold works, and when cross-validation can mislead in NLP.
- · Xiaojing Yang · Statistics
Effect Size: Statistical Significance Is Not Enough
A statistically significant result can still be too small to matter in research or deployment.
- · Xiaojing Yang · Machine Learning
Feature Engineering vs Representation Learning
How traditional ML features connect to embeddings, neural networks, and modern NLP systems.