Articles, newest first
Feature Engineering for Time Series Without Leaking the Future
Turning a time series into a tabular problem unlocks powerful models and introduces a specific failure: features that quietly contain information from the fu...
Read article
Weak Supervision for Better Machine Learning Labels
Weak supervision helps teams scale labeling by combining imperfect rules, heuristics, and external signals instead of hand-labeling every example.
Read article
Multiple Seasonality: MSTL, TBATS, and Fourier Terms
Hourly and daily data rarely has one season. Electricity demand cycles daily, weekly and annually at the same time, and a single seasonal period cannot repre...
Read article
Forecasting Baselines That Are Hard to Beat
An RMSE of 4.2 means nothing on its own. Without a baseline you cannot tell whether a model is skilful or merely arithmetic.
Read article
Multilevel Models for Operational Analytics
Multilevel models help analysts estimate group-level performance without overreacting to small samples or ignoring real differences between sites.
Read article
LLM Distillation Is Function Approximation, Not Model Copying
A smaller student model cannot inherit a larger teacher by osmosis. Distillation trains the student to approximate selected aspects of the teacher's behaviou...
Read article
Intermittent Demand Forecasting: Croston's Method and Its Successors
Spare parts and slow-moving stock produce series that are mostly zeros. Standard forecasters quietly fail on them; Croston's method and its successors are bu...
Read article
Missing Data Mechanisms in Machine Learning
Missing data is not only a preprocessing nuisance. The reason data is missing can change model bias, fairness, monitoring, and deployment behavior.
Read article
Cost-Sensitive Learning for Rare Event Prediction
Rare event models should be optimized for decisions, not only class balance. Cost-sensitive learning connects model thresholds to real operational consequences.
Read article
Decision Curve Analysis: Measuring Whether Predictive Models Are Worth Acting On
Decision curve analysis evaluates predictive models by asking whether acting on their predictions produces better decisions than simple alternatives.
Read article