![]() Then, you would save the preprocessed data in your local storage for applying ML algorithms. You use the data preprocessing tools provided in WEKA to cleanse the data. This data may contain several null values and irrelevant fields. If you observe the beginning of the flow of the image, you will understand that there are many stages in dealing with Big Data to make it suitable for machine learning −įirst, you will start with the raw data collected from the field. What WEKA offers is summarized in the following diagram − WEKA - an open source software provides tools for data preprocessing, implementation of several Machine Learning algorithms, and visualization tools so that you can develop machine learning techniques and apply them to real-world data mining problems.
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