Since the aggregated dataset consists of many features, the irrelevant features can be removed to reduce the computational time required for processing and analyzing data. Thus, the features having very low correlation with the output feature or very high correlation with other input features are excluded from this study. The linear correlation coefficient between pairs of the features Fp and Fq are calculated as Eq. (1):

where Fx,p (Fx,q) indicates the xth row of the feature Fp (Fq) and mp (mq) denotes the average of the feature Fp (Fq), respectively.

If two features Fp and Fq have low (high) correlation, Corr (Fp, Fq) tends to zero (− 1 or + 1).

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