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In this era of data science where R and Python are ruling the roost, let’s take a look at another data science tool called Weka. Weka has been around for fairly a while and was evolved internally at University of Waikato for research motive. What makes Weka worthy of try is the easy learning curve. The weka assignment help is there to answer all questions related to weka to make each and every student familiar with the subject. So Waikato Environment for Knowledge Analysis (Weka) developed at the University of Waikato, New Zealandgoes for a suite of machine learning software written in Java. It is free software licensed under the GNU General Public License.Together with graphical user interfaces, Weka includes a whip round of visualization tools and algorithms for data dissection and predictive modeling to gain easy access to these functions. The original non-Java version of Weka was a Tcl/Tk front-end to (mostly third-party) modeling algorithms implemented in other programming languages, plus data pre-processing utilities in C, and a Make file-based system for running machine learning experiments. This genuine version was primarily blocked out as a tool for analysing data from agricultural domains, but the more up to the minute, fully Java-based version (Weka 3), for which development started in 1997, is now used in droves of different application areas, in particular for educational purposes and experimentation. Through the weka assignment help one cannot only get the current details but also gain knowledge about its history.
Antiquity of weka
• In 1993, the University of Waikato in New Zealand began development of the original version of Weka, which became a mix of Tcl/Tk, C, and Make files.
• The decision of redeveloping Weka from scuff in Java, counting implementations of modeling algorithms was made in 1997.
• In 2005, Weka received the SIGKDD Data Mining and Knowledge Discovery Service Award.
• In 2006, Pentaho Corporation acquired an exclusive licence to use Weka for business intelligence. It forms the data mining and predictive analytics component of the Pentaho business intelligence suite.
The weka assignment help also throws light on the well-beings of weka. Thus Advantages of Weka includes:
• Free availability under the GNU General Public License.
• Portability, since it is fully implemented in the Java programming language and thus runs on almost any modern computing platform.
• A wide ranging collection of data pre-processing and reproducing techniques.
• Ease of use due to its graphical user interfaces.
Weka supports several standard data mining tasks, more specifically, data pre-processing, clustering, classification, regression, visualization, and feature selection. If the data is available as one flat file or relation, where each data point is defined by a fixed number of attributes, then all of the Weka’s capabilitiescan be predicated. Weka issues access to SQLdatabases operatingJava Database Connectivity andcan undertake the result returned by a database query.
Thus the weka assignment help lights up every single part of the weka software and makes it easy for every student.
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