Knowledge Discovery and Data Mining A Replicator Dynamics Approach to Collective Feature Engineering in Random Forests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Khaled Fawgreh, Mohamed Medhat Gaber and Eyad Elyan A Directed Acyclic Graph Based Approach to Multi-Class Ensemble Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Esra’a Alshda...

In this article we introduce Random Survival Forests, an ensemble tree method for the analysis of right censored survival data. As is well known, constructing ensembles from base learners, such as trees, can significantly improve learning performance. Recently, Breiman showed that ensemble learning can be further improved by injecting randomization into the base learning process, a method calle...

Extensions of binomial and multinomial formulae due to Abel, Cayley and Hurwitz are related to the probability distributions of various random subsets, trees, forests, and mappings. For instance, an extension of Hurwitz's binomial formula is associated with the probability distribution of the random set of vertices of a fringe subtree in a random forest whose distribution is de ned by terms of ...

Churn prediction is becoming a major focus of banks in China who wish to retain customers by satisfying their needs under resource constraints. In churn prediction, an important yet challenging problem is the imbalance in the data distribution. In this paper, we propose a novel learning method, called improved balanced random forests (IBRF), and demonstrate its application to churn prediction. ...

The use of random forests is increasingly common in genetic association studies. The variable importance measure (VIM) that is automatically calculated as a by-product of the algorithm is often used to rank polymorphisms with respect to their association with the investigated phenotype. Here we investigate a characteristic of this methodology that may be considered as an important pitfall, name...

Cardiac Arrhythmia refers to a medical condition in which heart beats irregularly. This paper aims to detect and classify arrhythmia into 14 different variants. A few popular techniques from contemporary literature were implemented namely Naive Bayes, feature selection, SVM, Random Forests and Neural Networks.A new approach combining SVM and Random Forests classifiers was also implemented.

7 Feature-space modelling 16 7.1 Theory of linear models . . . . . . . . . . . . . . . . . . . . . . 16 7.1.1 * Least-squares solution of the linear model . . . . . . . 17 7.2 Continuous response, continuous predictor . . . . . . . . . . . . 18 7.3 Continuous response, categorical predictor . . . . . . . . . . . . 23 7.4 * Multivariate linear models . . . . . . . . . . . . . . . . . . . . 25 7....

MOTIVATION There is great interest in pathway-based methods for genomics data analysis in the research community. Although machine learning methods, such as random forests, have been developed to correlate survival outcomes with a set of genes, no study has assessed the abilities of these methods in incorporating pathway information for analyzing microarray data. In general, genes that are iden...