Highlights
Data Exploration
• Data exploration techniques include the use of statistical descriptions and graphical visualisation.
• Most of the time in data mining projects is spent in data preprocessing.
• For data preprocessing to be successful, it is important to have an overall picture of the data.
• Appropriate data exploration techniques can support the data preprocessing steps as well as the choice of adequate data mining methods.
Data Preprocessing
• Data cleaning
• Involve work for filling in missing values, handling outliers, and resolving inconsistencies.
• Data transformation
• Convert data into forms that are appropriate for further analysis and data mining.
• Data reduction
• Reduce the volume of a dataset while maintaining the integrity of the original dataset.
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