Does Model Diversity Actually Matter in an ML Ensemble?Why combining different models doesn't guarantee a better ensemble: correlated errors, complementarity, underfitting, and validation on the full system.#Machine Learning#Ensemble Learning#Stacking#Model Validation#ExperimentationIbexcodeAugust 20, 2026
Machine Learning and Human Learning: Surprisingly Similar ProblemsMemorization, generalization, evaluation, errors, and redundant knowledge: what certain Machine Learning problems reveal about learning itself.#Machine Learning#Model Validation#Ensemble Learning#ExperimentationIbexcodeAugust 18, 2026
