A Case Study for Learning from Imbalanced Data Sets
作者： Aijun An , Nick Cercone , Xiangji Huang
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摘要: We present our experience in applying a rule induction technique to an extremely imbalanced pharmaceutical data set. focus on using variety of performance measures evaluate number quality measures. also investigate whether simply changing the distribution skew training can improve predictive performance. Finally, we propose method for adjusting learning algorithm environment. Our experimental results show that this adjustment improves formulas which coverage makes positive contributions value.
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sci-hub.st 参考文章(12)
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