hotSpot · HotSpot learns a set of rules (displayed in a tree-like structure) that maximize/minimize a target variable/value of interest. With a nominal target, one might want to look for segments of the data where there is a high probability of a minority value occuring (given the constraint of a minimum support). For a numeric target, one might be interested in finding segments where this is higher on average than in the whole data set. For example, in a health insurance scenario, find which health insurance groups are at the highest risk (have the highest claim ratio), or, which groups have the highest average insurance payout.

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• Latest Stable: 1.0.14.jar

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Version		Vulnerabilities	Size	Updated
1.0.x	hotSpot-1.0.14.jar		28.60 KB	Aug 09, 2021
	hotSpot-1.0.13.jar		28.59 KB	Aug 06, 2021
	hotSpot-1.0.12.jar		27.85 KB	Jul 26, 2021
	hotSpot-1.0.11.jar		26.47 KB	Jul 07, 2021
	hotSpot-1.0.10.jar		25.97 KB	Jun 29, 2021
	hotSpot-1.0.9.jar		25.92 KB	Jun 27, 2021
	hotSpot-1.0.8.jar		25.89 KB	Jun 09, 2021
	hotSpot-1.0.7.jar		25.77 KB	Jun 09, 2021
	hotSpot-1.0.6.jar		23.52 KB	Jun 02, 2021
	hotSpot-1.0.3.jar		22.04 KB	Apr 26, 2012
	hotSpot-1.0.2.jar		22.03 KB	Apr 24, 2012

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weka.associations

├─ weka.associations.HotSpot.class - [JAR]