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Implementation of Apriori Algorithm for calculation of frequent item sets and valid knowledge discoveries.
ndon/Apriori-Algorithm
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Following in an apriori algorithm implementation. Data needs to be in following format: 1 Bread Milk 2 Bread Diaper Beer Eggs 3 Milk Diaper Beer Coke 4 Bread Milk Diaper Beer 5 Bread Milk Diaper Coke Pointers: Everything is sepearated using tabs aka '\t'. Sample Name can be anything, it is ignored. No need to item column name or fixed number of columns. Possible to make the system more scalable. NOTE: Strings are used for manipulation instead of vectors/ints/arrays so that the system is easy to work for any type of data. Same test files are included. Asso.txt Asso1.txt Asso2.txt To test the file, Compile the Apriori.Java Run Apriori Type in the file name (with proper dirs if necessary) Enter the confidence and support (necessary for apriori algo) Enter any rule if needed. Ouput for the last two will be shown if part of data fits the criteria.
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Implementation of Apriori Algorithm for calculation of frequent item sets and valid knowledge discoveries.
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