Search Results for author:
Found 7 papers, 1 papers with code
Feature importance for machine learning redshifts applied to SDSS galaxies
When compared to the SDSS photometric redshifts, the RDF machine learning redshifts both decreases the standard deviation of residuals scaled by 1/(1+z) by 36% from 0. 066 to 0. 041, and decreases the fraction of catastrophic outliers by 57% from 2. 32% to 0. 99%.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics
Anomaly detection for machine learning redshifts applied to SDSS galaxies
We present an analysis of anomaly detection for machine learning redshift estimation.
Cosmology and Nongalactic Astrophysics
Measuring photometric redshifts using galaxy images and Deep Neural Networks
We propose a new method to estimate the photometric redshift of galaxies by using the full galaxy image in each measured band.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies Data Analysis, Statistics and Probability
Stacking for machine learning redshifts applied to SDSS galaxies
We observe a significant improvement of between 1. 9% and 21% on all computed metrics when stacking is applied to weak learners (such as SOMs and decision trees).
Learning from the machine: interpreting machine learning algorithms for point- and extended- source classification
The first is outputting and exploring the decision boundaries as given by decision tree based methods, which enables the visualization of the classification categories.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies Data Analysis, Statistics and Probability
The Buzzard Flock: Dark Energy Survey Synthetic Sky Catalogs
We show that the weak-lensing shear catalog, redMaGiC galaxy catalogs and redMaPPer cluster catalogs provide plausible realizations of the same catalogs in the DES Y1 data by comparing their magnitude, color and redshift distributions, angular clustering, and mass-observable relations, making them useful for testing analyses that use these samples.
Cosmology and Nongalactic Astrophysics
Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances and Weak Lensing
We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset.
Cosmology and Nongalactic Astrophysics
