2,017 research outputs found
Binary Classifier Calibration using an Ensemble of Near Isotonic Regression Models
Learning accurate probabilistic models from data is crucial in many practical
tasks in data mining. In this paper we present a new non-parametric calibration
method called \textit{ensemble of near isotonic regression} (ENIR). The method
can be considered as an extension of BBQ, a recently proposed calibration
method, as well as the commonly used calibration method based on isotonic
regression. ENIR is designed to address the key limitation of isotonic
regression which is the monotonicity assumption of the predictions. Similar to
BBQ, the method post-processes the output of a binary classifier to obtain
calibrated probabilities. Thus it can be combined with many existing
classification models. We demonstrate the performance of ENIR on synthetic and
real datasets for the commonly used binary classification models. Experimental
results show that the method outperforms several common binary classifier
calibration methods. In particular on the real data, ENIR commonly performs
statistically significantly better than the other methods, and never worse. It
is able to improve the calibration power of classifiers, while retaining their
discrimination power. The method is also computationally tractable for large
scale datasets, as it is time, where is the number of
samples
Warm Dark Haloes Accretion Histories and their Gravitational Signatures
We study clusters in Warm Dark Matter (WDM) models of a thermally produced
dark matter particle keV in mass. We show that, despite clusters in WDM
cosmologies having similar density profiles as their Cold Dark Matter (CDM)
counterparts, the internal properties, such as the amount of substructure,
shows marked differences. This result is surprising as clusters are at mass
scales that are {\em a thousand times greater} than that at which structure
formation is suppressed. WDM clusters gain significantly more mass via smooth
accretion and contain fewer substructures than their CDM brethren. The higher
smooth mass accretion results in subhaloes which are physically more extended
and less dense. These fine-scale differences can be probed by strong
gravitational lensing. We find, unexpectedly, that WDM clusters have {\em
higher} lensing efficiencies than those in CDM cosmologies, contrary to the
naive expectation that WDM clusters should be less efficient due to the fewer
substructures they contain. Despite being less dense, the larger WDM subhaloes
are more likely to have larger lensing cross-sections than CDM ones.
Additionally, WDM subhaloes typically reside at larger distances, which
radially stretches the critical lines associated with strong gravitational
lensing, resulting in excess in the number of clusters with large radial
cross-sections at the level. Though lensing profile for an
individual cluster vary significantly with the line-of-sight, the radial arc
distribution based on a sample of clusters may prove to be the
crucial test for the presence of WDM.Comment: 13 pages, 14 figures, submitted to MNRA
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