WEKA is an open source software written in java. Provides tools for data preprocessing, the application of various machine learning algorithms, and visualization tools. This allows you to develop machine learning techniques and apply them to data mining problems. The following diagram presented by WEKA is shown in:
Many features for making machine learning suitable for.
You will start with the raw data collected first. This data may contain several blank values and irrelevant fields. You use the data preprocessing tools provided in WEKA to clean up data.
You then save preprocessed data to your local storage to apply ML algorithms.
Note that under each category, WEKA ensures that several algorithms are implemented. Select an algorithm you want, set the parameters you want, and run them in the dataset.
Then, WEKA will give you the statistical output of model processing. Provides a visualization tool for you to examine data.
Various models can be applied to the same dataset. You can then compare the outputs of different models and choose what's best suited to your purpose.
Thus, the use of WEKA leads to faster development of machine learning models in general.