A classification tree generation device 10 that selects, from a plurality of classification condition candidates, a new classification condition to be added to a classification tree, which is a prediction model expressed in a tree structure formed from one or more nodes representing classification conditions, said device comprising: a first computation unit 11 that computes information gain relating to the classification condition candidate; a second computation unit 12 that computes, as a cost relating to the classification condition candidate, a value representing the magnitude of the smallest difference among differences between the classification condition candidate and each of the classification conditions included in the classification tree; and a selection unit 13 that selects, as the new classification condition, the classification condition candidate from among the plurality of classification condition candidates that has the largest value among values obtained by subtracting the computed cost from the computed information gain.
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