A proposal for PU classification under Non-SCAR using clustering and logistic model
The present study aims to investigate a cluster cleaning algorithm that is both computationally simple and capable of solving the PU classification when the SCAR condition is unsatisfied. A secondary objective of this study is to determine the robustness of the LassoJoint method to perturbations of the SCAR condition. In the first step of our algorithm, we obtain cleaning labels from 2-means clustering. Subsequently, we perform logistic regression on the cleaned data, assigning positive labels from the cleaning algorithm with additional true positive observations. The remaining observations are assigned the negative label. The proposed algorithm is evaluated by comparing 11 real data sets...
| Authors | Konrad Furmanczyk, Kacper Paczutkowski |
|---|---|
| Primary category | stat.ME |
| Published | 18 April 2026 |
| Last updated at source | 18 April 2026 |
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