You are familiar with Elasticsearch that is why you already considered Elasticsearch Java tutorial. In the tutorial, you get to know how it powers extremely fast searches, which ultimately supports your data discovery applications.
It is time that you focus on data mining. If you are an enterprise, you need data mining, which is the process of classifying through large data sets to find and establish relationships. This can help solve problems through data analysis. Basically, it allows enterprises to predict future trends.
There are many machine learning software intended to solve different data mining problems but you should focus on Weka (Waikato Environment for Knowledge Analysis). Here’s what you need to know about Weka
What is machine learning?
It is crucial that you know machine learning first. Machine learning is a type of artificial intelligence, which enables computers to learn the data without any assistance of explicit programs.
Its goal is to crawl through the data and find the patterns. Once patterns are found, it can adjust the program’s actions immediately. Actually, the machine learning method is similar to data mining. The only difference is how the systems extract the data.
How can Weka help?
Weka uses a collection of machine learning algorithms. The algorithms can be applied to data or from the Java code. Essentially, Weka is for regression, clustering, association, classification, visualisation, and data processing. The original version of Weka was primarily designed as a tool for analysing data from agricultural domains.
The more recent Java-based version is used in many different application areas particularly for research and educational purposes. Many consider this for its portability because it is fully implemented in Java, which can also run on almost any modern computing platform. It also boasts of a comprehensive collection of modeling and data preprocessing techniques.
Where to get Weka?
You can easily download Weka from its official website. After downloading, you simply execute commands (setenv WEKAHOME/ us/local/weka/weka-3-0-2 and setenv CLASSPATH $WEKAHOME/weka.jar: $CLASSPATH) at the command prompt. This is how to set the Weka environment variable for Java.
What are the features of Weka?
When you consider Weka Java tutorial, you get to know some of its features. Features of Weka include the following:
• The Weka platform is independent.
• It is an open source platform and free.
• It is easy to use.
• You get to enjoy many data processing tools.
• It is flexible for scripting experiments.
• It has a graphical user interface.
How about its application interfaces?
Weka has a total of five application interfaces. When you open Weka, it will start with the Weka GUI chooser screen. It is crucial that you know the different application interfaces for seamless use. The application interfaces include the following:
• Explorer: this interface can perform data mining tasks on raw data.
• Experimenter: this allows users to perform different experimental variations on datasets.
• Knowledge flow: it has an Explorer interface with drag and drop functionality. It can support incremental learning from the previous results.
• Simple CLI (Command Line Interface): the simple interface can be utilised for performing commands from a specific terminal.
• Workbench: this combines GUI (Graphical User Interface) into one.
What are the supported Weka data formats?
You must know that by default, Weka utilises ARFF (Attribute Relation File Format) for data analysis. There are other supported Weka data formats where data can be imported like CSV and OBDC.
What are the two parts of ARFF?
The ARFF has two parts – header and data section. The header section clearly defines the dataset name, attribute name, and type. The data sector, on the other hand, lists the instances of data. Basically, ARFF file needs the declaration of the attribute, relation, and data.
How to preprocess data?
It is a must to reprocess the data. There is a screen for choosing a file to be preprocessed. After loading the data in the Explorer, you can actually polish the data by choosing different options. You can remove or choose attributes depending on your need and even apply filters on data for a refined result.
There are three methods to infuse data for preprocessing. The methods include the following:
• Open-File: this will enable you to choose the file from the local machine.
• Open URL: this will allow you to choose the file from different locations.
• Pen database: this will allow you to retrieve data from a database source.
After considering Weka, you should also familiarise yourself with Ansible. You must know that Ansible is a configuration management system, which is written in Python. As soon as you consider Ansible tutorial PDF, you can automate the process of setting and installing software. Typically, Ansible is used with Linux-based nodes. However, it can also support Windows.