Data Mining Research Topics in Computer Science

Data Mining Research Topics in Computer Science

           Data Mining Research Topics in Computer Science is our enlightening service that is meant for the noble development of young minds. In this research, computer science topics can also be described as a wide range of project hub containing enormous topics. Our group of experts is also well versed in all the areas of data mining, and also they are constantly updating their knowledge in the respective field. Our Data Mining in Computer Science is our service create for students and research scholars. If you crave perfection, do approach us, as we also strive and attain perfection in everything we do.

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Mining Research Topics in Computer Science

           Data mining research topics in computer science is a broad spectrum that uses multiple algorithms. One of the most prominent algorithms also used in data mining is Weka. Over the years, many scholars also have done projects based on Weka and passed out with flying colors.

Multiple data mining tools and also concepts are analyzed with the help of Weka. In the field of web mining for outlier reduction, OWA expanded as operator based hybrid is enumerated with the help of WEKA. Many industries also used data mining implemented through WEKA as it has highly advanced features.

       ….“Weka can be explained as a series of the machine learning algorithm, which can be applied to a data set obtained from one’s own Java code. Weka leaves a permanent impression on the field of bioinformatics with its multiple application uses”.

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Our enigmatic team has put together a list containing all the topics that are also currently in trend in the area of Data Mining. They are as follows:

  • Neural Networks
  • Algorithms are also used to predict attacks
  • Classification
  • Clustering
  • Maintenance
  • Acquisition of risk knowledge
  • Artificial Intelligence also to Detect Attacks
  • Advanced Data Visualisation
  • Attribute Selection
  • Cost Estimation and also prediction analysis
  • Recognising attack patterns
  • Data Mitigation
  • Software risk management
  • And also in Association rule mining

Classifications of Data Mining Algorithms By its Task/Operations

  • Association Algorithms
  • Data Pre-processing Algorithms
  • Regression (Logistic and also Multiple)Algorithms
  • Sequence Analysis Algorithms
  • Segmentation Algorithms
  • Feature Selection also based on Algorithms
  • Classification Algorithms
  • Clustering Algorithms
  • Dimension Reduction also based on Algorithms
  • Filtering Algorithms
  • Prototype Generation also based in Algorithms
  • Time series Algorithms
  • Bagging Algorithms
  • Attribute Selection also based Algorithms
  • Feature Extraction Algorithms
  • Anomaly Detection also based on Algorithms
  • Statistical Analysis Algorithms

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