3 papers
cs.LG2025
Efficient Parameter Estimation for Bayesian Network Classifiers using Hierarchical Linear Smoothing
Connor Cooper, Geoffrey I. Webb, Daniel F. Schmidt
Bayesian network classifiers (BNCs) possess a number of properties desirable for a modern classifier: They are easily interpretable, highly scalable, and offer adaptable complexity…
cs.LG2025
Prevalidated ridge regression is a highly-efficient drop-in replacement for logistic regression for high-dimensional data
Angus Dempster, Geoffrey I. Webb, Daniel F. Schmidt
Logistic regression is a ubiquitous method for probabilistic classification. However, the effectiveness of logistic regression depends upon careful and relatively computationally e…
cs.LG2025
MONSTER: Monash Scalable Time Series Evaluation Repository
Angus Dempster, Navid Mohammadi Foumani, Chang Wei Tan +6
We introduce MONSTER-the MONash Scalable Time Series Evaluation Repository-a collection of large datasets for time series classification. The field of time series classification ha…