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In data mining and association rule learning, lift is a measure of the performance of a targeting model (association rule) at predicting or classifying cases as having an enhanced response (with respect to the population as a whole), measured against a random choice targeting model.
Overall, using confidence in association rule mining is great way to bring awareness to data relations. Its greatest benefit is highlighting the relationship between particular items to one another within the set, as it compares co-occurrences of items to the total occurrence of the antecedent in the specific rule.
Lift (data mining) Likelihood function; ... (data mining) Spurious relationship ... Wilks' theorem – redirects to section of Likelihood-ratio test; Winsorized mean ...
This data mining method has been explored in different fields including disease diagnosis, market basket analysis, retail industry, higher education, and financial analysis. In retail, affinity analysis is used to perform market basket analysis, in which retailers seek to understand the purchase behavior of customers.
In pattern recognition, information retrieval, object detection and classification (machine learning), precision and recall are performance metrics that apply to data retrieved from a collection, corpus or sample space. Precision (also called positive predictive value) is the fraction of relevant instances among the retrieved instances. Written ...
The odds ratio is generalized by the logistic model to model cases where the dependent variables are discrete and ... Lift (data mining) Mean dependence; Modifiable ...
Image source: Getty Images. 5. SSR Mining. Yes, there is a market for stocks beyond the technology sector!A fifth intriguing stock that has the potential to double your money in 2025 is precious ...
The TAR3 [6] [9] weighted contrast set learner is based on two fundamental concepts - the lift and support of a rule set. The lift of a set of rules is the change that some decision makes to a set of examples after imposing that decision (i.e., how the class distribution shifts in response to the imposition of a rule).