2 citations · 3 across the 4 of their papers we have counts for
4 papers
ARISE: An adaptive residual-informed stability ensemble for feature selection in small-sample biomedical omics
Zardad Khan, Amjad Ali, Naz Gul +2
Objective: Small-sample molecular classification requires feature selectors that identify predictive, stable, and nonredundant subsets for binary and multiclass outcomes. We propos…
A k nearest neighbours classifiers ensemble based on extended neighbourhood rule and features subsets
Amjad Ali, Muhammad Hamraz, Naz Gul +3
kNN based ensemble methods minimise the effect of outliers by identifying a set of data points in the given feature space that are nearest to an unseen observation in order to pred…
Optimal trees selection for classification via out-of-bag assessment and sub-bagging
Zardad Khan, Naz Gul, Nosheen Faiz +3
The effect of training data size on machine learning methods has been well investigated over the past two decades. The predictive performance of tree based machine learning methods…
Optimal survival trees ensemble
Naz Gul, Nosheen Faiz, Dan Brawn +3
Recent studies have adopted an approach of selecting accurate and diverse trees based on individual or collective performance within an ensemble for classification and regression p…