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A study of the Behavior of Several Methods for Balancing Machine Learning Training Data

A study of the Behavior of Several Methods for Balancing Machine Learning Training Data

A study of the Behavior of Several Methods for Balancing Machine Learning Training Data. Advisor ? Dr. Hsu Presenter ? Chien-Shing Chen Author: Gustavo E. A. P. A. Batista Ronaldo C. Prati Maria Carolina Monard. SigKDD,2004. Outline. Motivation Objective

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355 views • 35 slides
A Study of the Behavior of Several Methods for Balancing Machine Learning Training Data

A Study of the Behavior of Several Methods for Balancing Machine Learning Training Data

A Study of the Behavior of Several Methods for Balancing Machine Learning Training Data. Author: Gustavo E. A. Batista Presenter: Hui Li University of Ottawa. Contents. Introduction Why Learning from Imbalanced data sets might be difficult? 10 Methods Experimental Evaluation Conclusion.

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405 views • 35 slides
Methods of multivariate analysis for imbalance data problem

Methods of multivariate analysis for imbalance data problem

Methods of multivariate analysis for imbalance data problem. Under- and Oversampling Techniques Nikolai Gagunashvili (UNAK and MPIK). Four possibilities that can be used for solving imbalance data problem. Choice of appropriate classifier Use cost sensitive approach

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368 views • 22 slides
????? ??? ????? F-Measure, Kappa, Costs, MetaCost

????? ??? ????? F-Measure, Kappa, Costs, MetaCost

????? ??? ????? F-Measure, Kappa, Costs, MetaCost. ?"? ??? ???????. ??????. False Positives / Negatives. Confusion matrix 1. Confusion matrix 2. FN. Actual. Actual. FP. Predicted. Predicted. Precision (P) = 20 / 50 = 0.4 Recall (P) = 20 / 30 = 0.666 F-measure=2*.4*.666/1.0666=.5.

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310 views • 14 slides

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