Parameter Selection Strategy for Frequent Itemsets in Association Analysis
نویسندگان
چکیده
منابع مشابه
Discovering Frequent Closed Itemsets for Association Rules
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau...
متن کاملMining association rules using frequent closed itemsets
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau...
متن کاملFrequent closed itemsets based condensed representations for association rules
After more than one decade of researches on association rule mining, efficient and scalable techniques for the discovery of relevant association rules from large high-dimensional datasets are now available. Most initial studies have focused on the development of theoretical frameworks and efficient algorithms and data structures for association rule mining. However, many applications of associa...
متن کاملMining Association Rules in Graphs Based on Frequent Cohesive Itemsets
Searching for patterns in graphs is an active field of data mining. In this context, most work has gone into discovering subgraph patterns, where the task is to find strictly defined frequently re-occurring structures, i.e., node labels always interconnected in the same way. Recently, efforts have been made to relax these strict demands, and to simply look for node labels that frequently occur ...
متن کاملFrequent Itemsets for Genomic Profiling
Frequent itemset mining is a promising approach to the study of genomic profiling data. Here a dataset consists of real numbers describing the relative level in which a clone occurs in human DNA for given patient samples. One can then mine, for example, for sets of samples that share some common behavior on the clones, i.e., gains or losses. Frequent itemsets show promising biological expressiv...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: American Journal of Mathematical and Computer Modelling
سال: 2020
ISSN: 2578-8272
DOI: 10.11648/j.ajmcm.20200502.13