User interface and workflow for performing machine learning
AssigneeSymantec Corporation
InventorsPhillip DiCorpo, Shitalkumar S. Sawant, Sally Kauffman, Alan Dale Galindez, Sumesh Jaiswal, Ashish Aggarwal
Life of this patent
Estimating the term…
Abstract
A computing device receives a training data set that includes a plurality of positive examples of sensitive data and a plurality of negative examples of sensitive data. The computing device analyzes the training data set using machine learning to generate a machine learning-based detection (MLD) profile that can be used to classify new data as sensitive data or as non-sensitive data. The computing device computes a quality metric for the MLD profile.
Claims20
A method comprising:
- receiving, by a processing device, a training data set that includes a plurality of positive examples of sensitive data and a plurality of negative examples of sensitive data;
- receiving a selection of a memory allocation;
- analyzing, by the processing device, the training data set using machine learning to train a machine learning-based detection (MLD) profile, the MLD profile to be used to classify new data as sensitive data or as non-sensitive data;
- and
- computing, by the processing device, a quality metric for the MLD profile, the quality metric comprising a memory utilization rating, wherein the memory utilization rating complies with the memory allocation.
A non-transitory computer readable storage medium including instructions that, when executed by a processing device, cause the processing device to perform operations comprising:
- receiving, by the processing device, a training data set that includes a plurality of positive examples of sensitive data and a plurality of negative examples of sensitive data;
- receiving categorization information for the positive examples of sensitive data and for the negative examples of sensitive data;
- analyzing, by the processing device, the training data set using machine learning to train a machine learning-based detection (MLD) profile, the MLD profile to be used to classify new data as sensitive data or as non-sensitive data;
- computing, by the processing device, a quality metric for the MLD profile:
- and
- identifying categories of data to add to the training data set to improve the quality metric.
A computing device comprising:
- a memory to store instructions for a machine learning manager;
- and
- a processing device to execute the instructions, wherein the instructions cause the processing device to:
- receive a training data set that includes a plurality of positive examples of sensitive data and a plurality of negative examples of sensitive data;
- analyze the training data set using machine learning to train a machine learning-based detection (MLD) profile to be used to classify new data as sensitive data or as non-sensitive data;
- compute a quality metric for the MLD profile;
- determine that the quality metric fails to meet a quality threshold;
- modify the training data set;
- analyze the modified training data set to retrain the MLD profile;
- and
- compute a new quality metric for the MLD profile.
Dependencies are inferred from the claim text.