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. Data mining technologies are also offered, which obtains the needed information from a pool of information. We live in a world that recently undergoes a digital revolution. The base and source for the digital world are abundant data. As data is the base of everything, mining research topics becomes a universal field, which also never goes out of style. Our service also extends over a decade of innovation, constant updation, and satisfaction.

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Mining Research Topics

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

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 extraordinarily from our service. . . . . . .