Extracting the Frequent Item Sets by Using Greedy Strategy in Hadoop
نویسندگان
چکیده
منابع مشابه
Mining Fuzzy Frequent Item Sets
Due to various reasons transaction data often lack information about some items. This leads to the problem that some potentially interesting frequent item sets cannot be discovered, since by exact matching the number of supporting transactions may be smaller than the user-specified minimum. In this study we try to find such frequent item sets nevertheless by inserting missing items into transac...
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Data mining is the practice to search large amount of data to discover data patterns. Data mining uses mathematical algorithms to group the data and evaluate the future events. Association rule is a research area in the field of knowledge discovery. Many data mining researchers had improved upon the quality of association rule for business development by incorporating influential factors like u...
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In Text categorization techniques like Text classification or clustering, finding frequent item sets is an acquainted method in the current research trends. Even though finding frequent item sets using Apriori algorithm is a widespread method, later DHP, partitioning, sampling, DIC, Eclat, FP-growth, H-mine algorithms were shown better performance than Apriori in standalone systems. In real sce...
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ژورنال
عنوان ژورنال: IOSR Journal of Computer Engineering
سال: 2017
ISSN: 2278-8727,2278-0661
DOI: 10.9790/0661-1904018390