Classification tree models are simple and effective as software quality prediction models, and timely predictions of defects from such models can be used to achieve high software reliability.To evaluate the performance of the the suitable algorithms is applied to calculate the Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Receiver Operating Characteristic (ROC), Accuracy measure is are also applied. the above problem is implemented using Weka dataming tool ....etc

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Data mining techniques to automate software testing


Introduction:
Data mining
Data mining commonly involves four classes of tasks: Association rule learning – Searches for relationships between variables. For example a supermarket might gather data on customer purchasing habits. Using association rule learning, the supermarket can determine which products are frequently bought together and use this information for marketing purposes. This is someti ....etc

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for getting more details about each data mining project please browse through http://studentbank.in/topic-computer-science-project-ideas

1. Probabilistic Group Nearest Neighbor Queries in Uncertain Databases
2. A Web Usage Mining Framework for Evolving User Profiles in Dynamic Web Sites
3. A precise Termination Condition of the Probabilistic Packet Marking Algorithm
4. Watermarking Relational Databases Using Optimization-Based Techniques
5. Protection of Database Security via Collaborative Inference ....etc

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Hiii..i need information on the topic dataset technology query algorithm in streaming mining..please help me as i need ppt on this topic as soon as possible. ....etc

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Abstract: Spatial data mining algorithms heavily depend on the efficient processing of neighborhood
relations since the neighbors of many objects have to be investigated in a single run of a typical
algorithm. Therefore, providing general concepts for neighborhood relations as well as an efficient
implementation of these concepts will allow a tight integration of spatial data mining algorithms
with a spatial database management system. This will speed up both, the development and
the execution of spatial data mining algorithms. In ....etc

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Data Mining with Neural Networks and Genetic Algorithms
General Strategy
• Train Neural Network with representative data
• Use Genetic Algorithm to generate rule sets
• Evaluate performance of the rule sets
Training the Neural Network
• Only constraint on topology is that it must have the same number of inputs as categories (e.g., cap-shape, cap-surface, etc.) and the same number of outputs as classes (e.g., poisonous or edible)
• 3-layer perceptron appears to be model used for experiment with 7 ....etc

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please send me ppt of secure data collection in wireless sensor network using random routing algorithm
ppts for secure data collection in wireless sensor network using random routing algorith ....etc

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Algorithms and Issues In Client Software Design



Problem in choosing a local IP Address

When forming a connection endpoint, a client must choose a local IP address as well as a local protocol port number.
Host attaches to one network, the choice of a local IP address is trivial.
Routers or multi-homed hosts have multiple IP addresses, making the choice can be difficult.

Communicating With The Server Using TCP

Assuming connect call succeeds in establishing a connection , the client can use ....etc

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Please any one send me the java program for SPMining for effective pattern discovery ....etc

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