Method of and system for training machine learning algorithm for object classification
AssigneeServiceNow Canada Inc.
InventorsXiang ZHANG, Alexandre DROUIN
Life of this patent
Estimating the term…
Abstract
A system and non-transitory storage medium for performing object classification using a trained machine learning algorithm (MLA). The MLA includes an embedding layer and a classification layer. A byte representation of an object is received. A set of embedding indices is generated based on the byte representation of the object. The MLA embeds, using the embedding layer, the set of embedding indices to obtain an input vector and predicts an estimated class based on the input vector. In some implementations, the set of embedding indices is generated by parsing the byte representation to obtain byte n-grams and by applying a hash function on the byte n-grams.
Claims21
1-20. (canceled)
A system for predicting an estimated class of an object, the system comprising:
- a non-transitory storage medium storing computer-readable instructions thereon;
- and
- at least one processor operatively connected to the non-transitory storage medium,
- the at least one processor having access to a machine learning algorithm (MLA) having been trained to classify objects, the MLA comprising an embedding layer and a classification layer,
- the at least one processor, upon executing the computer-readable instructions, being configured for:
- receiving a byte sequence representation of the object;
- generating, based on the byte sequence representation, a set of embedding indices associated with the object;
- embedding, using the embedding layer of the MLA, the set of embedding indices to obtain an input vector representing the object;
- predicting, using the classification layer of the MLA, the estimated class for the object based on the input vector;
- and
- outputting the estimated class.
A non-transitory storage medium comprising computer-readable instructions stored thereon, the computer-readable instructions, upon being executed by at least one processor, cause the at least one processor to perform:
- accessing a machine learning algorithm (MLA) having been trained to classify objects, the MLA comprising an embedding layer and a classification layer,
- receiving a byte sequence representation of the object;
- generating, based on the byte sequence representation, a set of embedding indices associated with the object;
- embedding, using the embedding layer of the MLA, the set of embedding indices to obtain an input vector representing the object;
- predicting, using the classification layer of the MLA, an estimated class for the object based on the input vector;
- and
- outputting the estimated class.
Dependencies are inferred from the claim text.