Data Mining Topics for Project

Data Mining Topics for Project

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Let’s explore about Data Mining,

         …“Data mining is a process of attaining useful data from large pool sets for analyzing, discovering, exploring and also in the building.” Data mining models can be used for various application scenarios such as probability and risk analysis, forecasting, sequence finding, recommendations, and grouping.

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Key stages involving in Data Mining

  • Data Pre-processing
  • Feature Extraction
  • Feature-Selection
  • Feature Weighting
  • Discretization
  • Generation of Prototype
  • Instance Selection
  • And also in Data Classification

Filtering Techniques:

  • Function of filter include swap attribute values filter, Numeric Transform filter, Delete filter, Select filter, also in Replace Missing values filter, Add filter, and also in Merge Attribute filter, Nominal to binary filter.
  • It is used specifically for Normalisation, transforming, Combing, resampling and also transforming attributes.

Classification Techniques:

  • Logistic regression
  • Multi-layer perceptron’s
  • Gradient Boosted Decision Trees
  • Naïve Bayes Algorithm
  • And also in Kernel Principal Components Analysis

Clustering Schemes:

  • Cobweb
  • K-Means Algorithms
  • First farthest
  • Maximisation of expectation
  • X-Means Algorithms
  • Fuzzy-C-Means
  • And also in Spatially Constrained Fuzzy-C-Means

Support for Plugins and Tools

Plugins Support:

  • Entropy Triangle Package
  • Pentaho Data integration with also Weka
  • Pluggable evaluation metrics

Data mining Tools support:

  • IBM SPSS Miner
  • SAS EEnterprise Miner
  • R-Tool
  • And also in RapidMiner Rapid-I

Data Mining Topics

A set of research issues and research projects are crafted and also listed below especially for your reference.

  • Network anomaly detection
  • Categorisation and also text mining
  • Risk mining Acquisition
  • Web mining applications
  • Sentiment analysis
  • With learning algorithm attacks can also be predicted
  • By using pattern recognition attack trends can be determined
  • Advanced visualization also for attack analysis
  • Software risk management
  • Big data applications
  • Using data mining also for network setting
  • Creating unifying theory also for data mining
  • Levelling up data stream speed

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