Mixture Proportion Estimation for Positive--Unlabeled Learning via Classifier Dimension Reduction

01/30/2018
by   Zhenfeng Lin, et al.
0

Positive--unlabeled (PU) learning considers two samples, a positive set P with observations from only one class and an unlabeled set U with observations from two classes. The goal is to classify observations in U. Class mixture proportion estimation (MPE) in U is a key step in PU learning. In this paper, we show that PU learning is a generalization of local False Discovery Rate estimation. Further we show that PU learning MPE can be reduced to a one--dimensional problem via construction of a classifier trained on the P and U data sets. These observations enable application of methodology from the multiple testing literature to the PU learning problem. In particular we adapt ideas from Storey [2002] and Patra and Sen [2015] to address parameter identifiability and MPE. We prove consistency of two mixture proportion estimators using bounds from empirical process theory, develop tuning parameter free implementations, and demonstrate that they have competitive performance on simulated waveform data and a protein signaling problem.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/01/2021

Mixture Proportion Estimation and PU Learning: A Modern Approach

Given only positive examples and unlabeled examples (from both positive ...
research
06/21/2013

Class Proportion Estimation with Application to Multiclass Anomaly Rejection

This work addresses two classification problems that fall under the head...
research
02/19/2019

DEDPUL: Method for Mixture Proportion Estimation and Positive-Unlabeled Classification based on Density Estimation

This paper studies Positive-Unlabeled Classification, the problem of sem...
research
06/02/2023

Mixture Proportion Estimation Beyond Irreducibility

The task of mixture proportion estimation (MPE) is to estimate the weigh...
research
03/08/2016

Mixture Proportion Estimation via Kernel Embedding of Distributions

Mixture proportion estimation (MPE) is the problem of estimating the wei...
research
10/06/2015

Improved Estimation of Class Prior Probabilities through Unlabeled Data

Work in the classification literature has shown that in computing a clas...
research
02/10/2020

Towards Mixture Proportion Estimation without Irreducibility

Mixture proportion estimation (MPE) is a fundamental problem of practica...

Please sign up or login with your details

Forgot password? Click here to reset