WEKA is an open source software written in java. Data preprocessing provides tools for implementing various machine learning algorithms and visualization tools. Thus, you can develop machine learning techniques and apply them to data mining problems. What WEKA offers is shown in the following diagram:
Many features to make machine learning suitable.
You will start with the raw data collected first. This data may contain several empty values and irrelevant fields. You use the data preprocessing tools provided in WEKA to clean up the data.
Then you save preprocessed data to your local storage to implement ML algorithms.
Note that under each category, WEKA ensures that several algorithms are implemented. You select an algorithm that 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 the one that best suits your purpose.
Thus, the use of WEKA leads to the faster development of machine learning models in general.