Machine learning clustering of meteor observations produces a new hardness classification H_class that refines traditional Kb models using more parameters and reveals compositional structure in meteoroid populations.
In: International Conference on Machine Learning, pp
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
The Associativity-Peakiness metric provides higher dynamic range and computational efficiency than existing metrics for assessing clustering performance via contingency tables.
citing papers explorer
-
A Machine Learning Approach to Meteor Classification
Machine learning clustering of meteor observations produces a new hardness classification H_class that refines traditional Kb models using more parameters and reveals compositional structure in meteoroid populations.
-
Associativity-Peakiness Metric for Contingency Tables
The Associativity-Peakiness metric provides higher dynamic range and computational efficiency than existing metrics for assessing clustering performance via contingency tables.