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The operating core of recommender systems is based on the collaborative filtering stage, which, in current user to user recommender processes, usually uses the Pearson correlation metric.
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Results of the SCT were correlated the MCQ and OSCE using the Pearson correlation function.
The MEs were then correlated to relevant clinical traits using the Pearson correlation and Cox regression.
To correlate CPT values with DDI, y.CHR and HI, we used the Pearson correlation test.
For regression problems, we use the Pearson correlation coefficient [67].
Using the Pearson correlation method, the correlations among evaluated parameters were assessed.
The correlation between the two methods was calculated using the Pearson correlation coefficient.
Coexpression between interacting proteins was determined using the Pearson correlation coefficient r = 1 N ∑ i = 1.
Data was analysed by SPSS 16.0 software using the Pearson correlation of bivariate analysis.
The relationships among yield traits were measured using the Pearson correlation coefficient with the pairwise estimation method.
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