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We provide electrical projects based on power electronics, MATLAB Simulink and SIM Power
For Electronics Engineering Students we support technologies like ARM, GSM, GPS, RFID, Robotics, VLSI, NSL, NS3, OMNet++, OPNet, QUALNET, PeerSim
WEKA Projects is an acronym for Waikato environment for knowledge analysis. We offer weka academic projects for machine learning application and to extract valuable information from databases. We can develop various number of software application by weka tool. Our main aim of developing weka projects to ensure an innovative technology and to enhance an optiministic solution for data mining issues. We embed machine learning application to analyze computer program and large amount of data based on the concept of IEEE papers. We ensure efficient support to fast and give accurate decision making process. We develop research projects for research scholars and development in machine learning.
We adopt following features are:
To solve data mining problem we use weka tool. We follow various techniques in MS projects to implement weka projects are given as follows:
We provide various packages for different technique in Weka and described as:
Java Neural Network Package: Weka plug in implemented by java.
HMMWEKA: library function contain hidden Markov learning algorithm.
Provide semi supervised learning algorithm and collective classification algorithm.
LTBDBC: classification with clustering and dynamic selection algorithm.
Clustering composed of following packages.
We use packages are:
XAPRIORI: we use this package to select frequent item in pattern mining algorithm.
Snowball Stemmers: we use this to wrap snowball stemmer into weka working model in snowball stemmer algorithm.
NLP: we use NLP package to construct part of speech filter and Penn tree Bank tokenize.
Using a weka tool, we deployed more than 75+ projects with various applications. We provided the Weka advantages are: