WOA-Miner: Classification Rule Discovery Using Whale Optimization Algorithm

Extensions to the Ant-Miner Classification Rule Discovery Algorithm

Prediction of Breast Tumor Malignancy Using Neural Network and Whale Optimization Algorithms (WOA)

Introduction: Breast cancer is the most prevalent cause of cancer mortality among women. Early diagnosis of breast cancer gives patients greater survival time. The present study aims to provide an algorithm for more accurate prediction and more effective decision-making in the treatment of patients with breast cancer. Methods: The present study was applied, descriptive-analytical, based on the ...

Classification Rule Discovery with Ant Colony Optimization

In [9], we presented a modified version of Ant-Miner (i.e. Ant-Miner2), where the core computation heuristic value was based on a simple density estimation heuristic. In this paper, we present a further study and introduce another ant-based algorithm, which uses a different pheromone updating strategy and state transition rule. By comparison with the work of Parpinelli et al, our method can imp...

Classification of Microcalcifications Using Multi-Dimensional Genetic Association Rule Miner

Breast cancer is a most common disease diagnosed in women. The Microcalcification Clusters (MCs) in the mammograms are one of the important early sign. The accurate detection of microcalcifications is a key problem in Computer Aided Detection (CAD). In this paper, we have proposed a novel association rule mining approach for classification of microcalcifications. Initially, the shape features a...

Max-Miner Algorithm Using Knowledge Discovery Process in Data Mining

Discovering frequent item sets is an important key problem in data mining applications, such as the discovery of association rules, strong rules, episodes, and minimal keys. Typical algorithms for solving this problem operate in a bottom-up, breadth-first search direction. The computation starts from frequent itemsets (the minimum length frequent itemsets) and continues until all maximal (lengt...