Weka Machine Learning: Why It Is The Jack Of All Trades?

Weka machine learning is one of the fastest ML libraries and a great tool for data scientists. The University of Waikato developed it for research purposes. Weka is one of the best machine learning software which offers access through a GUI (graphical user interface). It is one of the best terminal application for Java API. To develop any standard machine learning project it offers hundreds of built-in software. Weka provides transparent access to all the machine learning software like R, Deeplearning4j, scikit-learn, and Python.

What is Weka Machine Learning?

Weka ( Waikato Environment for Knowledge Analysis) is a free machine learning software which offers various visualization tool for predictive modeling and data analysis. It is a collection of machine learning algorithms for predictive research and data mining.

What is Weka Machine Learning If you want to perform big data migration you can use this best machine learning software. You can apply the software to any dataset directly through own java code. The University of Waikato developed this tool for expert data scientists.

Why it is the Jack of All Trades?

Weka is considered as the jack of all trades because of its beautiful features. It supports all the operating systems and devices. You can implement all of the machine learning algorithms with these machine learning tools. You can apply Weka machine learning directly to any dataset. It has a strong connection to any other library. You can implement this library to your project. So FossGuru is telling it a jack of all trades.

What You Can Do With it?

What you can do with WekaWeka machine learning can be used for many purposes. You can apply it to various machine learning methods and techniques. Some of the most common uses of this machine learning library are:

  • pre-processing
  • classification
  • regression
  • clustering
  • association rules
  • visualization

Who can use Weka Machine Learning?

Weka machine learning is just a collaboration tool. It allows its users to evaluate and run a machine learning project with very little knowledge. It is suitable for newbies and students. If you are a non-IT student you also can use the Weka ML tool.

Features of Weka ML

Features of the ML

  • Weka is such an ML software which is developed by a famous university.
  • It is developed by Java Programming.
  • It is free to use under the GNU General Public License.
  • You can run it to almost all modern cloud computing platform. 
  • The data modeling and processing techniques of Weka are very rich.
  • Weka offers a graphical user interface so it is very easy to use.
  • With the help of Java database connectivity, you can access to SQL database if you use Weka.
  • It is very suitable for developing any new machine learning platform.

Setting up Weka Environment

If you want to use the Weka machine learning tool you have to set the Weka environment. To download the Weka ML software have to visit the GitHub website. In this site, you will get details instructions for installing the Weka environment. It will show you details for each operating system.

Algorithms of Weka

Weka machine learning software has various algorithms. Because of its huge number of the algorithm, it becomes one of the best and rich machine learning libraries. It supports all the machine learning algorithm which I described earlier. 

Graphical User Interface of Weka

Weka offers a component-based Knowledge Flow interface to the data scientist. It offers a collection of the dataset that can be compared with others. The main user interface of it is Explorer. Several components of Weka workbench are:

Preprocess panel

The Preprocess panel offers a comma-separated values (CSV) file and import data from the database. Then it processes and applies to filter algorithm. This filtering algorithm is capable to transform, delete and manage the data.

Classify panel

The Classify panel is used to apply the regression and classification algorithm to estimate the accuracy of the predictive model. It can visualize the prediction that can help to classify the model.

Associate panel

The Associate panel is for accessing association rule learners that can manage the relationship between various attributes of data.

Cluster panel

The Cluster panel is used for clustering the model. k-means algorithm is one of the famous examples of it. For the normal distribution, it can use the expectation-maximization algorithm.

Select attributes panel

This Select attributes panel is used for predicting most predictive attributes.

Visualize panel

The Visualize panel is used for the scatter plot matrix. Here, the individual scatters plot can be used for various purposes.

What is Weka Native Regression Tools

What is Weka Native regression toolsWeka supports many classification and regression tools. The Weka Native regression tools are executable within the software. But if it is non-native it needs the support of the R.Weka environment. Some of the regression tools are M5Rules, DecisionStump, M5P, RandomForest, REPTree, ZeroR, and LinearRegression.

Weka is used for prediction and calculation by the data scientist. So as the machine learning engineer you must know some relevant machine learning tools. Some of them are:


Scikit-learn is one of the best machine learning libraries of Python ML language. You can use the library for classification and regression.


RapidMiner is used for commercial machine learning framework. It is implemented with Java to integrate for various functions. 


Orange is used for data mining and visualization. You can use this free and open-source machine learning project.

Neural Designer

Neural Designer is one of the best data mining software that is used for deep learning. This ML library is written in C programming language.

Massive Online Analysis

This free and opensource machine learning software is used for large scale data mining schemes. It is developed by the same developer of the Weka machine learning tool.


Knime is one of the best machine learning and data mining software for prediction. This ML tool is also implemented with Java.


Auto-WEKA is one of the best ML tools used by ML engineers. You can also use this automated machine learning system.

Expert’s Opinion of Weka Machine Learning

Weka is the collection of machine learning algorithms. The algorithm can be applied to any dataset directly. It is widely used for data mining tasks. The tools of Weka are capable of data pre-processing, regression, classification, clustering and visualization. To develop any machine learning scheme it is well suited. Weka is an open source so you have full freedom. Because of the graphical user interface is very easy to use. Weka is the best choice of experts because it is developed by a renowned University of New Zealand.

Weka is Machine Learning Without Programming

Weka is used to develop a machine learning pipeline. It allows you to evaluate and run the program without much machine learning knowledge. Java API is used to implement all of its projects. With the help of WekaDeeplearning4j Weka can be used well.

What Weka Support to Execute

Weka supports almost all the operating systems. You can integrate it with the most popular data science tool. It can be developed, evaluate and run with the help of the R programming language. Python is one of the best supportive tools for the Weka machine learning tool. Spark can be used to use a truly large dataset of Weka.

Final Thought

Weka machine learning is the collection of all the algorithms of machine learning. It is used to solve real-life data mining problems. This java written tool can support all the operating systems and devices. You can apply the Weka ML tool to any dataset directly. So it is one of the best choices of machine learning experts.

Download and More Information

Hawlader's passion for technology has driven him to be an avid writer for over 16 years. His vast knowledge of the Windows and Android operating systems is a testament to his proficiency in the field. In addition to his expertise in open source software, he also possesses an extensive understanding of the open-source platform, making him a valuable resource for technology enthusiasts. His contributions to FossGuru writers with research-based articles have helped readers to stay up-to-date with the latest trends in the tech industry. Furthermore, Hawlader's curiosity for scientific breakthroughs has led him to be a keen reader of science blogs, keeping him informed about the latest developments in the field.

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