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Weka stands for Waikato Environment for Knowledge Analysis. Weka is a flightless bird. It is a popular machine learning software and is written in JAVA. This software was developed at the University of Waikato, New Zealand. Weka is a free software and is licensed under the GNU General Public License. The original Weka was a non-java version and was primarily designed as a tool for analysation of data from agricultural domains. The recent version is fully java based (Weka 3) and is used in many different areas. The development of the new version started in 1997. It is mainly used in educational and research fields. There are various advantages of Weka.
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The product of Weka can be better described and studied from Weka Assignment Help.
• This software is freely available under GNU General Public License.
• As Java is platform independent, Weka runs on almost all modern computing platforms. In other words it is portable software.
• It is very simple and easy to use due to its graphical user interface.
• It comprises a huge collection of data analysing tools which are also used in modelling techniques.
Various processes that is supported by Weka is data mining tasks, clustering, data pre-processing, classifications, visualization, regression and feature selection. The main interface of Weka is the Explorer. It can be clearly and properly understood by the materials provided by Weka Assignment Help Online.
There are a lot of technical entities involved in the interfaces and background of Weka, one of its most important interfaces is explorer, however it uses another interface called Flow interface which is a knowledge based interface, it also uses the command line.
The Interface has certain layers to go through such as:-
• There are many processes involved before the final outcome, which are called pre-processes, in this process data is driven from different storage locations to another, and it uses a filtering algorithm for carrying out this pre-processing. They also carry out many other specific functions such as deleting instances.
• Another important panel called the classify panel regulates and operates classification and regression algorithm to control the data flow accuracy. They also have been involved in predictions of the outcomes.
• A minor panel called the associate panel is involved with maintain relationships between the data and its processes.
• There is panel to judge the clustering tools used in Weka and it is called Cluster Panel.
• Other Panel and tools include visual panel and many other attributes used in Weka.
The Detail uses and procedure about the working of Weka can be learnt from Weka Assignment Help.
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