Weka Tutorial

Weka - Feature Selection
When a database contains a large number of attributes, there will be several attributes which do not become significant in the analysis that you are currently seeking. Thus, removing the unwanted attributes from the dataset becomes an important task in developing a good machine learning model.
Discuss Weka
Weka is a comprehensive software that lets you to preprocess the big data, apply different machine learning algorithms on big data and compare various outputs. This software makes it easy to work with big data and train a machine using machine learning algorithms. This tutorial will guide you in the
Weka - Useful Resources
The following resources contain additional information on Weka. Please use them to get more in-depth knowledge on this.
Weka - Quick Guide
The foundation of any Machine Learning application is data - not just a little data but a huge data which is termed as Big Data in the current terminology.
Weka - Association
It was observed that people who buy beer also buy diapers at the same time. That is there is an association in buying beer and diapers together. Though this seems not well convincing, this association rule was mined from huge databases of supermarkets. Similarly, an association may be found between
Weka - Clustering
A clustering algorithm finds groups of similar instances in the entire dataset. WEKA supports several clustering algorithms such as EM, FilteredClusterer, HierarchicalClusterer, SimpleKMeans and so on. You should understand these algorithms completely to fully exploit the WEKA capabilities.

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