Discussion question 1 – data mining clinical application
When tackling this challenge, I would apply a variety of data mining techniques such as clustering, classification and association rules. Clustering is used to uncover patterns or groupings within the dataset so that similar observations can be grouped together for further analysis. Classification helps distinguish between different classes of observations based on their characteristics which can then be used to make predictions about future outcomes. Finally, association rules identify relationships between variables that allow for more accurate forecasting.
Specific techniques I would not use include regression analysis or time series models as they are not suitable for this type of problem since no historical data is available. Additionally these methods focus on linear relationships which do not always provide an accurate reflection of complex data sets.
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