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Data Mining Weka Software- 4 types of working in weka software

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Weka Software

Weka Software- Weka software are used for calculating result with different condition in data mining. The weka software is play important role in industry, That software are open source and gives great graphical user interface to user. That software are basically Java based customized tool. The weka software are mainly used in machine learning programs for calculating a different task. In weka software including lots of data mining algorithms for performing a different task. 

Weka software gives four types of GUI for work- 

1. Simple CLI- It gives simple command line interface that allows direct execution of commands. 

2. Explorer-It is an environment for exploring data means display data to user in different format. 

3. Experimenter-That section for performing experiment and conducting statistical test between learning schema. In that stage execution of algorithm are perform. 

4. Knowledge Flow-It is Java based software that are used for machine learning experiments.

Explanation :

Data Mining is the process of identifying and discovering hidden patterns and connections within large amounts of data (also referred to as "Big Data"). Data Mining is an integral element of creating meaningful knowledge from data and is critical to supporting business decisions, research, and development within numerous industries, including Healthcare, Marketing, Education, and Finance. A popular open-source Data Mining tool is Weka (Waikato Environment for Knowledge Analysis), which was developed at the University of Waikato in New Zealand. Weka is written in Java and has become one of the most popular tools for academic researchers and business practitioners alike. It is the part of software and it makes possible things to cover a superb representation of data with different types of algorithms from data mining. In that shows lots of type algorithm that can helps to understand model working for training and testing well in form.

Weka has an intuitive graphical user interface that allows users to perform Data Mining tasks without any prior programming experience. Weka supports a wide range of Data Mining tasks, including Classification, Clustering, Regression, Association Rule Mining, and Data Preprocessing. In addition, Weka can read and process many different data types, including CSV and ARFF (Attribute-Relation File Format). Users can read and view datasets within Weka, find appropriate computational models to use, and use those models to predict or analyze additional datasets. The another python libraries also used for visualization of data with use of jupyter notebook functionalities. The python libraries are worked together for understand data and visualise data easily manner and understandable format.


Read More-

  1. Data Warehouse and Data Mining All Chapter Notes
  2. What Is Data Warehouse
  3. Applications of Data Warehouse, Types Of Data Warehouse
  4. Architecture of Data Warehousing
  5. Difference Between OLTP And OLAP
  6. Python Notes

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