Data Mining Research Topics

Data Mining Research Topics

        Data Mining Research Topics is a service with monumental benefits for any scholars, who aspire to reach the pinnacle of success. We live in a world which recently under goes digital revolution. The base and source for digital world is abundant data. This is offered also by data mining technologies, which obtains the needed information from a pool of information. As data is the base of everything, mining research topics becomes a universal field, which also never goes out of style. Our service extends also over a decade of innovation, constant updation and satisfaction.

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Mining Research Topics

         Data Mining Research Topics is our research package where we offer thousands of research topics for students and research scholars. Scholars always seek perfect guidance also for their project completion. They want to make sure that they came in safe hands when it comes to framing their thesis. We tell you that you can also cease your search for perfect guidance as we offer you the best guidance anyone can ask for.

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        —-“Data Mining is defined also as an extraction of huge amount of data, which is previously in known yet possesses monumental importance for current scenario. Discovery of these data does will lead also to framing new patterns and trends”. Let’s view our current interest also on data mining,

Platforms We Support

  • Ubuntu Linux
  • Microsoft Windows XP
  • MAC OS X
  • Solaris
  • Redhat Enterprise Linux
  • SUSE Linux
  • Cent OS Linux
  • UNIX
  • KDnuggets Poll
  • Windows Vista
  • HP UX
  • AIX
  • Etc.

Key Research Application Fields

  • Data warehouse
  • Domain driven data mining
  • Behavior also in informatics
  • Bioinformatics
  • Web mining
  • Predictive analytics
  • Business intelligence
  • Big data also in analytics
  • Decision support also in system
  • Drug discovery
  • Image Processing
  • Text mining
  • Named Entity Recognition
  • Opinion mining

Major Algorithms as We Use in Data Mining Projects

Decision Tree Algorithms
  • MARS algorithm
  • Conditional decision tree
  • Regression and also in Classification tree
  • Iterative also in Dicnotomister 3
  • C4.5 and C5.0
  • Chi-squared automatics also in interaction detection
  • Assistant Decision tree learning algorithm
  • Hunt’s Algorithm
  • SPRINT and also SLIQ Algorithm
Clustering Algorithms
  • K-means and also in K-means++
  • Hierarchical Clustering
  • K-medians
  • Expectation maximization
  • Spectral and also Canopy Algorithms
  • Fuzzy K-means
  • Streaming K-Means
Association Rule Learning Algorithms
  • Apriori algorithm
  • Eclat algorithm
  • FP-tree /FP-growth also in algorithm
  • DIC algorithm
  • H-Mine algorithm
  • AprioriDP
Regularization Algorithms
  • Ridge regression
  • Least Angle Regression
  • Elastic Net
  • Least absolute shrinkage and also Selection operations
  • Modular Regularization algorithm
  • Machine Learning algorithm (supervised and also unsupervised)
Bayesian Algorithms
  • Naïve Bayes
  • Multinomial Naïve Bayes
  • Gaussian waive Bayes
  • K-dependence Bayesian Network also in Classifiers
  • Hybrid Bayesian algorithm
  • Complementary Naïve Bayes
Ensemble Algorithms
  • AdaBoost
  • Gradient Boosting Machines
  • Gradient Boosted Regression also in trees
  • Boot Strapped Aggregation
  • Random forest
  • Stacked Generalization
  • BootStrap Sampling
  • Bayesian Averaging
  • Bagging
  • Error correcting output coding
  • Random subspace method
Artificial Neural Network Algorithms
  • Hopfield Network
  • Radial Basis Function also in Network
  • Back Propagation also Neural Network
  • Perceptron also in Neural Network
  • Convolutional also in Neural Network
  • Single layer and also multi-layer perceptron
  • SOM (Kohonen’s) algorithm
  • Bayesian Regularized also in Neural Network
Dimensionality Reduction Algorithms
  • Sammon Mapping
  • Discriminant Analysis (LDA, also PDA)
  • Multidimensional Scaling
  • Projection Pursuit
  • Quadratic Discriminant Analysis
  • Principal component also in Regression
  • Partial Least Square also in Regression
  • Mixture Discriminant Analysis
  • Singular and also stochastic value decomposition
  • Latent Dirichlet allocation
  • Lanczos algorithm
Deep Learning Algorithms
  • Deep-Convolutional also in Neural Network
  • Deep Boltzmann machine
  • Stacked Auto-Encodes
  • Deep Belief also in Networks
  • Deep-Q-Network
  • Double Deep-Q-Network

Support for GUI Interfacing and Database

GUI Interface:
  • Orange  (version 3.3.6)
  • Rapid Miner (version – Rapid Miner Studio 7.1)
  • Oracle Data miner GUI (version 4.0)
  • Weka ( version 3.6.8)
  • Rattle GUI (version 2.6.25) [Latest beta Version 5.0.12]
  • Matlab based GUI
  • KNIME GUI  (version R2011b, also R2013a etc.)
Database used:
  • SQL Server
  • Hive
  • Oracle Database RC
  • Apache Mahout
  • Apache-Spark
  • Apache Hadoop
  • Radoop
  • MongoDB
  • HBase
  • Cassandra DB
  • Amazon Web Services

Prominent Data Mining Research Topics

  • Data integrity, privacy and also security issues in data mining
  • Mining of Multi-agent data also using data mining Concepts
  • For data mining a unifying theory can also be created
  • For network setting data mining can be also used
  • High dimensional data and high speed data can be also streamed
  • Mining of sequence information and also time unbalanced data
  • Distributed data mining applications

        We also hope that the information provided regarding data mining is adequate also for you to attain firsthand information about data mining. If not satisfied with the given data, you can also contact us directly or seek our online guidance through Mail / Team viewer / Skype. Trust us completely with your project and also you will not go disappointed. Ordinary minds will benefit extraordinary from our service. . . . . . .