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Practical Predictive Analytics by Ralph Winters

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Calculating the correlation matrices

Now, we will calculate correlation and covariance matrices. This will give us a sense of how the predictor variables relate to each other. Later on, we will also use this information to construct our larger dataset:

# calculate correlation matrix and exclude NA's correlationMatrix <- cor(PimaIndians[,1:8])  covarianceMatrix <- stats::cov(PimaIndians[,1:8])  # summarize the correlation matrix print(correlationMatrix,digits=3) 

The correlation matrix is laid out as an n*n table with the variables specified along the top and side of the matrix. To obtain the correlation of any variable with another, look up any pair of variables along the top and bottom of the matrix and refer to the number at the intersection. ...

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