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## An Efficient Algorithm for Mining Frequent Patterns full reportPosted by: project topics Created at: Monday 05th of April 2010 09:50:32 AM Last Edited Or Replied at :Friday 16th of December 2011 10:14:15 PM | mining frequent spatio temporal sequential patterns ,
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so the dataset shrinks and gives us quite small conditional frequent pattern base. From this
database the frequent patterns are generated. Existing system: Traditional system based on the manual calculation and dynamic counting method. Very difficult to find frequent patterns from the large transaction using manual calculation. Dynamic Item set counting method contains very complex procedure. So it is difficult to implement. DIC (Dynamic Item set Counting) algorithm which uses more database scan, presents a new approach for finding large item sets. Aim of the DIC algorithm is improving the .................. [:=> Show Contents <=:] | |||

## apriori algorithm gui applet frame implementation in java codePosted by: Created at: Saturday 03rd of November 2012 01:23:35 PM Last Edited Or Replied at :Saturday 03rd of November 2012 01:23:35 PM | apriori algorithm using asp net ,
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## apriori algorithm gui applet frame implementation in java codePosted by: Created at: Saturday 03rd of November 2012 01:05:14 PM Last Edited Or Replied at :Saturday 03rd of November 2012 01:05:14 PM | java code apriori,
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i just love this camera :). it is very light. its zoom is very good .................. [:=> Show Contents <=:] | |||

## apriori algorithm code in java free downloadPosted by: Created at: Saturday 13th of October 2012 10:29:33 PM Last Edited Or Replied at :Wednesday 13th of March 2013 04:55:07 AM | apriori project in java download ,
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## Fraud Detection in High Voltage Electricity Consumers Using Data MiningPosted by: Wifi Created at: Thursday 28th of October 2010 01:41:26 PM Last Edited Or Replied at :Thursday 28th of October 2010 01:41:26 PM | Mining,
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month to one of the clusters found by the SOM (4 or 5 weeks per month); 5. Verify if each new week adequately fits into the cluster that it was attributed (fitness), or if this week probably represents a new profile unknown until now; 6. Verify if the unknown profile is justified by modifications of the consumer contract, keeping approximately constant the reason between monthly registered electrical demand and contracted electrical demand (RD/CD = k). Fig. 2.3.1 Flowchart indicating the steps of the behavior analysis of each consumer, each new month. The flowchart presented on Fig................... [:=> Show Contents <=:] | |||

## Data Mining On Multimedia DataPosted by: seminarsonly Created at: Monday 20th of September 2010 07:19:09 AM Last Edited Or Replied at :Saturday 22nd of January 2011 01:03:57 AM | multimedia data compression format ,
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My SQL Operating system : LINUX/ Windows IDE : Net Beans HARDWARE SPECIFICATION Processor : Pentium IV OR Above Primary Memory : 256 MB RAM Storage .................. [:=> Show Contents <=:] | |||

## An Efficient Algorithm for Mining Frequent Patterns full reportPosted by: project topics Created at: Monday 05th of April 2010 09:50:32 AM Last Edited Or Replied at :Friday 16th of December 2011 10:14:15 PM | mining frequent spatio temporal sequential patterns ,
mining frequent itemsets from uncertain data,
mining frequent itemsets ,
mining frequent patterns associations and correlations,
mining frequent patterns without candidate generation ,
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oftware much easier and effectively. With the compiler, first we translate a program into an
intermediate language called Java bytecodes ---the platform-independent codes interpreted by the
interpreted on the Java platform. The interpreter parses and runs each Java bytecode instruction on
the computer. Compilation happen s just once; interpretation occurs each time the program is
executed. Java bytecodes can be thought as the machine code instructions for the Java Virtual Machine (JVM). Every Java interpreter, whether itâ„¢s a development tool or a web browser that can run applets, is a.................. [:=> Show Contents <=:] | |||

## Signed Approach for Mining Web Content OutliersPosted by: project report tiger Created at: Monday 01st of March 2010 11:54:39 AM Last Edited Or Replied at :Wednesday 20th of July 2011 11:05:55 PM | mining web informative structures and contents based on entropy analysis ,
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n broadly fall into following categories: A. Distribution based methods are conducted by the
statistics community. These methods deploy some known distribution model and detect as outliers
points that deviate from the model. B. Depth based algorithms organize objects in convex hull layers
in data space according to peeling depth and outliers expected to be with shallow depth values. C.
Deviation based techniques detect outliers by checking the characteristics of objects and identify
an object as that deviates these features as outlier. D. Distance based algorithms give a rank to
all points..................[:=> Show Contents <=:] |

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