Which technique of Artificial Intelligence (AI)/Statistical is used ‘to see…

In statistics and data mining, techniques are broadly grouped by the kind of insight they produce: some techniques CLASSIFY or PREDICT a category, some SEARCH/OPTIMIZE across possibilities, and some measure how one variable or data point RELATES to another. A technique that quantifies the strength and direction of the relationship between two variables — producing a single coefficient, typically between -1 and +1 — is a correlation technique.

The question asks for the technique used 'to see how one piece of data is linked to another piece of data.' This is precisely what correlation measures: it tells us whether two variables increase together, move in opposite directions, or show no relationship at all, without altering or classifying either variable.

Contrasting this with the other offered techniques, by what each one actually does:

• Decision Tree — a supervised-learning technique that recursively splits data into branches using attribute-based tests, to classify records into categories or predict an outcome value.

• Genetic Algorithms — an optimization/search technique inspired by natural selection (using selection, crossover and mutation operators) to search a large solution space for a near-optimal answer.

• Fuzzy Tree — a decision-tree style structure that uses fuzzy-logic membership functions instead of crisp either/or splits, used for classification when category boundaries are not sharply defined.

None of these three is defined by measuring the link between two separate data points the way correlation is. So the technique described in the question is Correlation.