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Table 6 Data Selection

From: Predicting academic success in higher education: literature review and best practices

Methods

When to use

Advantages

Disadvantages

Vertical selection

To remove redundant or irrelevant features

Facilitate understanding of the extracted pattern and rises the speed of the learning stage

Requires a good understanding of the data domain

Horizontal selection

To remove redundant and/or conflicting instances

Enhance the quality of input data, thus enable improved performance of DM models

In descriptive analysis, it is best to have as many instances as possible.