Does historical context shape younger citizens' propensity for unconventional forms of participation?Key findings Of all measures of political participation we explored, voter turnout is the main ...

Ordinal regression (OR, also called ordinal classification) is classification of ordinal data, in which the underlying target variable is categorical and considered to have a natural ordinal relation ...

We developed a classifier to infer acute ischemic stroke severity from Medicare claims using the modified Rankin Scale at discharge. The classifier can be used to improve stroke outcomes research and ...

The current implementation of type_of_target in scikit-learn classifies any 1D array of integer-like values with more than two unique values as 'multiclass', even when the data is actually count or ...

ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...

ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...

In this episode of eSpeaks, Jennifer Margles, Director of Product Management at BMC Software, discusses the transition from traditional job scheduling to the era of the autonomous enterprise. eSpeaks’ ...

Ordinal regression, or classification with ordered classes, naturally arises for a lot of problems where the target label are discrete preferences. This can be starts (X out of 5), ratings (X of out ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on this powerful machine learning technique used to predict a single numeric value. A regression problem is one ...

The Ordinals protocol was introduced to Bitcoin in early 2023 at a most opportune time. Bitcoin had nearly two years of low transaction fees from the lack of demand to actually send Bitcoin ...