TAILIEUCHUNG - Comparing Association Rules and Decision Trees for Disease Prediction

Association rules represent a promising technique to find hidden patterns in a medical data set. The main issue about mining association rules in a medical data set is the large number of rules that are discovered, most of which are irrelevant. Such number of rules makes search slow and interpretation by the domain expert difficult. In this work, search constraints are introduced to find only medically significant association rules and make search more efficient. In medical terms, association rules relate heart perfusion measurements and patient risk factors to the degree of stenosis in four specific arteries. Association rule medical significance is evaluated with the usual support and confidence metrics, but also lift | Comparing Association Rules and Decision Trees for Disease Prediction Carlos Ordonez University of Houston Houston TX USA ABSTRACT Association rules represent a promising technique to find hidden patterns in a medical data set. The main issue about mining association rules in a medical data set is the large number of rules that are discovered most of which are irrelevant. Such number of rules makes search slow and interpretation by the domain expert difficult. In this work search constraints are introduced to find only medically significant association rules and make search more efficient. In medical terms association rules relate heart perfusion measurements and patient risk factors to the degree of stenosis in four specific arteries. Association rule medical significance is evaluated with the usual support and confidence metrics but also lift. Association rules are compared to predictive rules mined with decision trees a well-known machine learning technique. Decision trees are shown to be not as adequate for artery disease prediction as association rules. Experiments show decision trees tend to find few simple rules most rules have somewhat low reliability most attribute splits are different from medically common splits and most rules refer to very small sets of patients. In contrast association rules generally include simpler predictive rules they work well with user-binned attributes rule reliability is higher and rules generally refer to larger sets of patients. Categories and Subject Descriptors Database Management Database Applications Data Mining Computer Applications Life and Medical Sciences Health General Terms Algorithms Experimentation Keywords Association rule decision tree medical data Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full .

• Báo cáo khoa học
• Association Rules
• Decision Trees
• Disease Prediction
• DEFINITIONS
• Search Constraints
• Medical Data
• Frequent itemsets
• Closed frequent itemsets
• Closed itemset lattice
• Association rules with constraints
• Constraint mining
• High utility itemsets
• High utility itemset lattice
• High utility association rules
• Mining high utility association rules
• Efficient algorithm
• Data mining
• Multi criteria analysis
• Multi agent system
• Non redundant rules
• Thermodynamic Models
• Industrial Applications
• From Classical
• Advanced Mixing Rules
• Association Theories
• Basketball Association
• Official Rules
• Court Dimensions
• History of Basketball
• Professional Basketball
• Common Basketball
• Nghiên cứu Datamining microsoft server 2005
• Thuật toán microsoft association rules
• Microsoft decision tree
• Đồ án tốt nghiệp Công nghệ thông tin
• Khai thác dữ liệu
• Thuật toán khai thác dữ liệu
• Khai mở dữ liệu
• Bài giảng Khai mở dữ liệu
• Luật kết hợp
• Tính chất của subset
• Building CPI forecasting model
• Combining the smooth transition regression model
• Mining association rules
• CPI forecasting model
• The price changes of merchandises
• Closed lattice
• GenMax algorithm
• Bài giảng Máy học nâng cao
• Máy học nâng cao
• Thuật toán Apriori
• Mô hình hóa bài toán
• BMC Bioinformatics
• Multi omics experiments
• R package
• Data integration
• Information technology
• Information technology doctoral thesis
• Mining fuzzy association rules
• Linguistic information
• Mathematical foundation for informatics
• Hội thảo khoa học Công nghệ thông tin và truyền thông
• Information and Communication technology conference 2022
• Supporting association consultancy
• National high school exam
• Consulting system
• Temporal quantitative databases
• Summary of Computer doctoral thesis
• Computer doctoral
• Fuzzy sequential patterns
• Association rules mining
• Rank Sort MDPREF Algorithm
• Preference rules
• Preference mining
• User profile mining
• Compressed transactions
• Knowledge discovery
• Hedge algebras
• Functional dependency
• Conditional functional dependency
• Association rule
• Data dependencies
• Unified hierarchy for FDs
• Lecture Data mining
• Bài giảng Khai thác dữ liệu
• Association rule mining
• Computational complexity
• Genome wide association studies
• Complex diseases
• Single nucleotide polymorphism
• Structured GWAS data
• Gene sequencing technology
• Mining Multiple level Association Rules Based
• Benchmarking the Data
• Using Data Mining to Investigate
• A Novel Model for Global Customer
• Clustering Parallel Data Streams
• Content based Image Classification via
• Alternative Techniques
• training data
• Simple models
• Logistic regression
• chest pain
• low grade pyrexia
• loss of appetite
• paravertebral abscess
• empyema thoracis
• pleural effusion
• Therapeutic Potential
• Principles and Application
• Thyroid Cancer Research
• Worldwide Trends
• Infectious Disease
• Research Revealed
• Khai phá dữ liệu
• Overview of data mining
• Other Data Mining problems
• Applications of data mining