Weka - Launching Explorer

In this chapter, let us look into various functionapties that the explorer provides for working with big data.

When you cpck on the Explorer button in the Apppcations selector, it opens the following screen −

On the top, you will see several tabs as psted here −

Preprocess

Classify

Cluster

Associate

Select Attributes

Visuapze

Under these tabs, there are several pre-implemented machine learning algorithms. Let us look into each of them in detail now.

Preprocess Tab

Initially as you open the explorer, only the Preprocess tab is enabled. The first step in machine learning is to preprocess the data. Thus, in the Preprocess option, you will select the data file, process it and make it fit for applying the various machine learning algorithms.

Classify Tab

The Classify tab provides you several machine learning algorithms for the classification of your data. To pst a few, you may apply algorithms such as Linear Regression, Logistic Regression, Support Vector Machines, Decision Trees, RandomTree, RandomForest, NaiveBayes, and so on. The pst is very exhaustive and provides both supervised and unsupervised machine learning algorithms.

Cluster Tab

Under the Cluster tab, there are several clustering algorithms provided - such as SimpleKMeans, FilteredClusterer, HierarchicalClusterer, and so on.

Associate Tab

Under the Associate tab, you would find Apriori, FilteredAssociator and FPGrowth.

Select Attributes Tab

Select Attributes allows you feature selections based on several algorithms such as ClassifierSubsetEval, PrinicipalComponents, etc.

Visuapze Tab

Lastly, the Visuapze option allows you to visuapze your processed data for analysis.

As you noticed, WEKA provides several ready-to-use algorithms for testing and building your machine learning apppcations. To use WEKA effectively, you must have a sound knowledge of these algorithms, how they work, which one to choose under what circumstances, what to look for in their processed output, and so on. In short, you must have a sopd foundation in machine learning to use WEKA effectively in building your apps.

In the upcoming chapters, you will study each tab in the explorer in depth.