Performance of evaluation metrics for classification in imbalanced data
This paper investigates the effectiveness of various metrics for selecting the adequate model
for binary classification when data is imbalanced. Through an extensive simulation study …
for binary classification when data is imbalanced. Through an extensive simulation study …
New links for binary regression: an application to coca cultivation in Peru
Binary response data arise naturally in applications. In general, the well-known logistic and
probit regression models form the basis for analyzing binary data in practice. These …
probit regression models form the basis for analyzing binary data in practice. These …
Power and reversal power links for binary regressions: An application for motor insurance policyholders
In binary regression, symmetric links such as logit and probit are usually considered as
standard. However, in the presence of unbalancing of ones and zeros, these links can be …
standard. However, in the presence of unbalancing of ones and zeros, these links can be …
Fixing imbalanced binary classification: An asymmetric Bayesian learning approach
Most statistical and machine learning models used for binary data modeling and
classification assume that the data are balanced. However, this assumption can lead to poor …
classification assume that the data are balanced. However, this assumption can lead to poor …
Flexible cloglog links for binomial regression models as an alternative for imbalanced medical data
The complementary log‐log link was originally introduced in 1922 to RA Fisher, long before
the logit and probit links. While the last two links are symmetric, the complementary log‐log …
the logit and probit links. While the last two links are symmetric, the complementary log‐log …
Performance of asymmetric links and correction methods for imbalanced data in binary regression
A de la Cruz Huayanay, JL Bazan… - Journal of Statistical …, 2019 - Taylor & Francis
In binary regression, imbalanced data result from the presence of values equal to zero (or
one) in a proportion that is significantly greater than the corresponding real values of one (or …
one) in a proportion that is significantly greater than the corresponding real values of one (or …
Identifiability and bias reduction in the skew-probit model for a binary response
DH Lee, S Sinha - Journal of Statistical Computation and …, 2019 - Taylor & Francis
The skew-probit link function is one of the popular choices for modelling the success
probability of a binary variable with regard to covariates. This link deviates from the probit …
probability of a binary variable with regard to covariates. This link deviates from the probit …
Cryopreservation of Prunus padus seeds: emphasising the significance of Bayesian methods for data analysis
Conservation of Prunus padus L., a tree of high ecological and pharmacological importance,
has been evaluated by storing seeds at subzero (− 20° C and− 80° C) and cryogenic (− 196° …
has been evaluated by storing seeds at subzero (− 20° C and− 80° C) and cryogenic (− 196° …
Regression models for binary data with scale mixtures of centered skew-normal link functions
For the binary regression, the use of symmetrical link functions are not appropriate when we
have evidence that the probability of success increases at a different rate than decreases. In …
have evidence that the probability of success increases at a different rate than decreases. In …
Longitudinal binary response models using alternative links for medical data
A de la Cruz Huayanay, JL Bazán… - Brazilian Journal of …, 2023 - projecteuclid.org
Motivated for a medical data about schizophrenia symptoms where an imbalanced binary
response is observed, we introduce a broad class of link functions, called power and reverse …
response is observed, we introduce a broad class of link functions, called power and reverse …