公开(公告)号：US20230267339A1

公开(公告)日：2023-08-24

申请号：US17675202

申请日：2022-02-18

申请人： International Business Machines Corporation

发明人： Dzung Tien Phan ,  Connor Aram Lawless ,  Jayant R. Kalagnanam ,  Lam Minh Nguyen ,  Chandrasekhara K. Reddy

IPC分类号： G06N5/02

CPC分类号： G06N5/022

摘要： In unsupervised interpretable machine learning, one or more datasets having multiple features can be received. A machine can be trained to jointly cluster and interpret resulting clusters of the dataset by at least jointly clustering the dataset into clusters and generating hyperplanes in a multi-dimensional feature space of the dataset, where the hyperplanes separate pairs of the clusters, where a hyperplane separates a pair of clusters. Jointly clustering the dataset into clusters and generating hyperplanes can repeat until convergence, where the clustering in a subsequent iteration uses the generated hyperplanes from a previous iteration to optimize performance of the clustering. The hyperplanes can be adjusted to further improve the performance of the clustering. The clusters and interpretation of the clusters can be provided, where a cluster's interpretation is provided based on hyperplanes that construct a polytope containing the cluster.