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An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption

CVPR 2018 · Learning theory and algorithms › Sample complexity · approach: Density and property estimation · 44 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use MPEIA rather than ED for estimating the class priorPNU(SL) on Magic · Magicmisclassification rate: 17.7 (1.8) -> 16.4 (1.0)Helped
Use MPEIA rather than ED for estimating the class priorPNU(SL) on SUSY · SUSYestimated positive class prior: 0.3992 -> 0.2040Helped
Use MPEIA rather than KM for estimating the class priorPNU(SL) on SUSY · SUSYmisclassification rate: 20.2 (0.3) -> 24.4 (2.4)Hurt
Use MPEIA rather than ED for estimating the class priorPNU(SL) on Waveform · Waveformestimated positive class prior: 0.3407 -> 0.1892Helped
Use MPEIA rather than ED for estimating the class priorPNU(SL) on Waveform · Waveformmisclassification rate: 15.2 (0.9) -> 9.2 (1.4)Helped
Use MPEIA rather than KM for estimating the class priorPNU(SL) on ijcnn1 · ijcnn1estimated positive class prior: 0.1096 -> 0.4509Hurt
Use MPEIA rather than ED for estimating the class priorPNU(SL) on ijcnn1 · ijcnn1misclassification rate: 36.9 (5.8) -> 36.4 (5.4)No clear effect
Use MPEIA rather than ED for estimating the class priorPNU(SL) on Spambase · Spambaseestimated positive class prior: 0.3178 -> 0.2909Helped
Use MPEIA rather than PE for estimating the class priorPNU(SL) on Spambase · Spambasemisclassification rate: 13.3 (2.6) -> 14.8 (0.9)Hurt
Use MPEIA rather than KM for estimating the class priorPNU(SL) on a9a · a9aestimated positive class prior: 0.2062 -> 0.1990Helped
Use MPEIA rather than KM for estimating the class priorPNU(SL) on a9a · a9amisclassification rate: 18.1 (1.1) -> 18.1 (0.9)No clear effect
Use MPEIA rather than KM for estimating the class priorPNU(SL) on w8a · w8aestimated positive class prior: 0.3109 -> 0.2833Helped

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