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An Efficient Algorithm for Mining Frequent Patterns


Posted by: sivakesava574
Created at: Friday 20th of January 2012 01:22:33 AM
Last Edited Or Replied at :Friday 20th of January 2012 01:22:33 AM
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An Efficient Algorithm for Mining Frequen..................[:=> Show Contents <=:]



An Efficient Algorithm for Mining Frequent Patterns full report


Posted 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
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ne item Based on minimum support threshold
Apriori algorithm works as follows:
¢ The first step, Apriori algorithm generates Candidate 1 “ item sets.
Then, item sets count and minimum support value are compared to find
the set L1 (frequent item sets).
¢ The second step, algorithm use L1 to construct the set C2 of
Candidate 2 “ item sets. The process is finished when there are no more
candidates.
4. FP Growth Tree Generation:
This modules generates the frequent patterns based on FP growth
Algorithm. And also it generates the FP Tree to find out the frequent patterns..................[:=> Show Contents <=:]



An Efficient Algorithm for Mining Frequent Patterns full report


Posted 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
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save considerable amounts of memory for storing the transactions. The basic idea of the FP-growth algorithm can be described as a recursive elimination scheme: in a preprocessing step delete all items from the transactions that are not frequent individually, i.e., do not appear in a user-specified minimum number of transactions. Then select all transactions that contain the least frequent item (least frequent among those that are frequent) and delete this item from them.
Advantages of FP-Growth:
Only 2 passes over data-set
Compresses data-set
No candidate generation
Much faster than..................[:=> Show Contents <=:]



MiningFrequentPatternsfromLargeDatabasesUsingCountdistributionalgorithm


Posted by: mechanical engineering crazy
Created at: Thursday 27th of August 2009 04:00:33 PM
Last Edited Or Replied at :Thursday 27th of August 2009 04:00:33 PM
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arameters may be appropriate. Before using the algorithm we first preprocess the data. We implemented Count Distribution Algorithm for finding frequent patterns from transactional databases. We implemented Partition Algorithm to partition the database. The Count Distribution Algorithm is a simple parallelization of Apriori. All processors generate the entire candidate hash tree from item set. Each processor can thus independently get partial supports of the candidates from its local database partition. Next, the algorithm does a sum reduction to obtain the global counts by exchanging lo..................[:=> Show Contents <=:]



An efficient algorithm for iris pattern recognition using 2 download seminar report


Posted by: Computer Science Clay
Created at: Thursday 30th of July 2009 07:03:40 AM
Last Edited Or Replied at :Thursday 30th of July 2009 07:03:40 AM
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n of this method under the platforms of MATLAB.

http://www.seminarprojects.net/downloads/?file=/computer%20science%20and%20electronics/AN-EFFICIENT- ALGORITHM-FOR-IRIS-PATTERN-RECOGNITION-U.pdf&name=AN-EFFICIENT-ALGORITHM-FOR-IRIS-PATTERN-RECOGNITIO N-U.pdf..................[:=> Show Contents <=:]



An Efficient Algorithm for iris pattern


Posted by: computer science crazy
Created at: Tuesday 07th of April 2009 01:22:31 PM
Last Edited Or Replied at :Tuesday 03rd of August 2010 01:10:29 AM
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peed compared to other methods. With a strong scientific approach and mathematical background we have developed an algorithm to facilitate the implementation of this method under the platforms of MATLAB


IMAGES - An introduction:

A dictionary defines image as a reproduction or representation of the form of a person or thing. The inherent association of a human with the visual senses, predisposes one to conceive an image as a stimulus on the retina of the eye, in which case the mechanism of optics govern the image formation resulting in continuos range, multi-tone images.

A digital ..................[:=> Show Contents <=:]



An Efficient Algorithm for iris pattern Recognition using 2D Gabor Wavelet


Posted by: Computer Science Clay
Created at: Sunday 01st of March 2009 02:24:03 AM
Last Edited Or Replied at :Sunday 01st of March 2009 02:24:03 AM
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hermore, when biometrics measures are applied in combination with other controls, such as access cards or passwords, the reliability of authentication controls takes a giant step forward.

BIOMETRICS-AN OVERVIEW:
Biometrics is best defined as measurable physiological and/or behavioral characteristics that can be utilized to verify the identity of an indivisual. They include the following:
Iris scanning
Facial recognition
Fingerprint verification
Hand geometry
Retinal scanning
Signature verification
Voice verification

ADVANTAGES OF THE IRIS IDENTIFICATION:
Highly p..................[:=> Show Contents <=:]



An Efficient Algorithm for iris pattern Recognition using 2D Gabor Wavelet Trans


Posted by: computer science crazy
Created at: Sunday 21st of September 2008 01:06:40 AM
Last Edited Or Replied at :Saturday 09th of March 2013 05:46:32 AM
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BIOMETRICS-AN OVERVIEW:
Biometrics is best defined as measurable physiological and/or behavioral characteristics that can be utilized to verify the identity of an indivisual. They include the following:
Iris scanning
Facial recognition
Fingerprint verification
Hand geometry
Retinal scanning
Signature verification
Voice verification

ADVANTAGES OF THE IRIS IDENTIFICATION:
Highly protected internal organ of the eye.
Iris patterns possess a high degree of randomness.
Variability: 244 degrees of freedom.
Entropy: 3.2 bits per square millimetre.
Uniquenes..................[:=> Show Contents <=:]



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