2 citations · 4 across the 9 of their papers we have counts for
9 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…
A Random Projection k Nearest Neighbours Ensemble for Classification via Extended Neighbourhood Rule
Amjad Ali, Muhammad Hamraz, Dost Muhammad Khan +2
Ensembles based on k nearest neighbours (kNN) combine a large number of base learners, each constructed on a sample taken from a given training data. Typical kNN based ensembles de…
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…
Comparative Analysis of Machine Learning Approaches to Analyze and Predict the Covid-19 Outbreak
Muhammad Naeem, Jian Yu, Muhammad Aamir +3
Background. Forecasting the time of forthcoming pandemic reduces the impact of diseases by taking precautionary steps such as public health messaging and raising the consciousness…
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…