Efficient Classification Rule Mining for Breast Cancer Detection

2016 ◽  
pp. 50-63
Author(s):  
Sufal Das ◽  
Hemanta Kumar Kalita
Keyword(s):  
Breast Cancer ◽  
Genetic Algorithm ◽  
Association Rule ◽  
Breast Cancer Detection ◽  
Classification Rule ◽  
Classification Rules ◽  
Optimal Solutions ◽  
Rule Mining ◽  
Detect Breast Cancer ◽  
Binary Strings

Breast cancer is the second largest cause of cancer deaths among women. Mainly, this disease is tumor related cause of death in women. Early detection of breast cancer may protect women from death. Various computational methods have been utilized to enhance the diagnoses procedures. In this paper, we have presented the genetic algorithm (GA) based association rule mining method which can be applied to detect breast cancer efficiently. In this work, we have represented each solution as chromosome and applied to genetic algorithm based rule mining. Association rules which imply classification rules are encoded with binary strings to represent chromosomes. Finally, optimal solutions are found out by develop GA-based approach utilizing a feedback linkage between feature selection and association rule.

Association Rule Mining for Job Shop Scheduling Problem Based on Genetic Algorithm

2012 ◽  
Vol 629 ◽  
pp. 730-734 ◽  
Author(s):  
Cun Liang Yan ◽  
Wei Feng Shi
Keyword(s):  
Genetic Algorithm ◽  
Association Rule ◽  
Association Rule Mining ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Rule Mining ◽  
Concept Hierarchy ◽  
Shop Scheduling

Job shop scheduling problem (JSP) is the most typical scheduling problem, In the process of JSP based on genetic algorithm (GA), large amounts of data will be produced. Mining them to find the useful information is necessary. In this paper dividing, hashing and array (DHA) association rule mining algorithm is used to find the frequent itemsets which contained in the process, and extract the corresponding association rules. Concept hierarchy is used to interpret the rules, and lots of useful rules appeared. It provides a new way for JSP study.

Two-level parallel CPU/GPU-based genetic algorithm for association rule mining

2020 ◽  
Vol 22 (2/3) ◽  
pp. 335
Author(s):  
Leila Hamdad ◽  
Zakaria Ournani ◽  
Karima Benatchba ◽  
Ahcène Bendjoudi
Keyword(s):  
Genetic Algorithm ◽  
Association Rule ◽  
Association Rule Mining ◽  
Rule Mining

Ant Miner

2020 ◽  
Vol 10 (1) ◽  
pp. 45-59
Author(s):  
Bijaya Kumar Nanda ◽  
Satchidananda Dehuri
Keyword(s):  
Data Mining ◽  
Large Data ◽  
Classification Rule ◽  
Classification Rules ◽  
Rule Mining ◽  
Ant Colonies ◽  
Benchmark Datasets ◽  
Objective Classification ◽  
Single Objective ◽  
Better Than

In data mining the task of extracting classification rules from large data is an important task and is gaining considerable attention. This article presents a novel ant miner for classification rule mining. The ant miner is inspired by researches on the behaviour of real ant colonies, simulated annealing, and some data mining concepts as well as principles. This paper presents a Pittsburgh style approach for single objective classification rule mining. The algorithm is tested on a few benchmark datasets drawn from UCI repository. The experimental outcomes confirm that ant miner-HPB (Hybrid Pittsburgh Style Classification) is significantly better than ant-miner-PB (Pittsburgh Style Classification).

scholarly journals Hedyotis diffusaCombined withScutellaria barbataAre the Core Treatment of Chinese Herbal Medicine Used for Breast Cancer Patients: A Population-Based Study

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yuan-Chieh Yeh ◽  
Hsing-Yu Chen ◽  
Sien-Hung Yang ◽  
Yi-Hsien Lin ◽  
Jen-Hwey Chiu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Herbal Medicine ◽  
Association Rule ◽  
Association Rule Mining ◽  
Breast Cancer Patients ◽  
Rule Mining ◽  
The Core ◽  
Chinese Herbal ◽  
Hedyotis Diffusa ◽  
Treat Breast Cancer

Traditional Chinese medicine (TCM), which is the most common type of complementary and alternative medicine (CAM) used in Taiwan, is increasingly used to treat patients with breast cancer. However, large-scale studies on the patterns of TCM prescriptions for breast cancer are still lacking. The aim of this study was to determine the core treatment of TCM prescriptions used for breast cancer recorded in the Taiwan National Health Insurance Research Database. TCM visits made for breast cancer in 2008 were identified using ICD-9 codes. The prescriptions obtained at these TCM visits were evaluated using association rule mining to evaluate the combinations of Chinese herbal medicine (CHM) used to treat breast cancer patients. A total of 37,176 prescriptions were made for 4,436 outpatients with breast cancer. Association rule mining and network analysis identifiedHedyotis diffusaplusScutellaria barbataas the most common duplex medicinal (10.9%) used for the core treatment of breast cancer.Jia-Wei-Xiao-Yao-San(19.6%) andHedyotis diffusa(41.9%) were the most commonly prescribed herbal formula (HF) and single herb (SH), respectively. Only 35% of the commonly used CHM had been studied for efficacy. More clinical trials are needed to evaluate the efficacy and safety of these CHM used to treat breast cancer.

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