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Association Rule Mining algorithms operate on a data matrix (e.g., customers products) to derive rules 2, 22]. We propose a single-pass algorithm for mining linear rules in such a matrix based on Principal Component Analysis. PCA detects correlated columns of the matrix, which correspond to, e.g., products that sell together. The rst contribution of this(More)
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