Understanding deep learning models
AssigneeTelefonaktiebolaget LM Ericsson (publ)
InventorsPerepu SATHEESH KUMAR, SARAVANAN M
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Abstract
A method for explaining deep-learning models is provided. The method includes extracting a set of features from a first deep-learning model for a first set of training data; clustering the set of features into N groups, wherein N represents a number of unique labels in the first set of training data; forming a clustering matrix from the N groups; and determining dominant columns in the clustering matrix to form a subset of the set of features.
Claims19
A method for explaining deep-learning models, the method comprising:
- extracting a set of features from a first deep-learning model for a first set of training data;
- clustering the set of features into N groups, wherein N represents a number of unique labels in the first set of training data;
- forming a clustering matrix from the N groups;
- and
- determining dominant columns in the clustering matrix to form a subset of the set of features.
A node adapted for explaining deep-learning models, the node comprising:
- a data storage system;
- and
- a data processing apparatus comprising a processor, wherein the data processing apparatus is coupled to the data storage system, and the data processing apparatus is configured to:
- extract a set of features from a first deep-learning model for a first set of training data;
- cluster the set of features into N groups, wherein N represents a number of unique labels in the first set of training data;
- form a clustering matrix from the N groups;
- and
- determine dominant columns in the clustering matrix to form a subset of the set of features.
A node comprising:
- an extracting unit configured to extract a set of features from a first deep-learning model for a first set of training data;
- a clustering unit configured to cluster the set of features into N groups, wherein N represents a number of unique labels in the first set of training data;
- a forming unit configured to form a clustering matrix from the N groups;
- and
- a determining unit configured to determine dominant columns in the clustering matrix to form a subset of the set of features.
Dependencies are inferred from the claim text.