2 citations · 2 across the 5 of their papers we have counts for
5 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…
Centroid Decision Forest
Amjad Ali, Saeed Aldahmani, Hailiang Du +1
This paper introduces the centroid decision forest (CDF), a novel ensemble learning framework that redefines the splitting strategy and tree building in the ordinary decision trees…
Feature Selection via Robust Weighted Score for High Dimensional Binary Class-Imbalanced Gene Expression Data
Zardad Khan, Amjad Ali, Saeed Aldahmani
In this paper, a robust weighted score for unbalanced data (ROWSU) is proposed for selecting the most discriminative feature for high dimensional gene expression binary classificat…
POSSE-kNN: Pathwise Out-of-Bag Selected Subspace Ensembles for Binary Classification
Zardad Khan, Amjad Ali, Najd Adeed +1
Nearest neighbour classification is attractive for tabular data, but its performance can deteriorate when a fixed query centred neighbourhood does not follow the local class geomet…
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…