Data set cleaning for artificial neural network training
AssigneeMacronix International Co., Ltd.
InventorShih-Hung Chen
Life of this patent
Estimating the term…
Abstract
A technology for cleaning a training data set for a neural network using dirty training data starts by accessing a labeled training data set that includes relatively dirty labeled data elements. The labeled training data set is divided into a first subset A and a second subset B. The procedure includes cycling between the subsets A and B, including producing refined model-filtered subsets of subsets A and B to provide a cleaned data set. Each refined model-filtered subset can have improved cleanliness and increased numbers of elements.
Claims20
A computer-implemented method for cleaning training data for a neural network, comprising:
- accessing a labeled training data set;
- using a first subset of the labeled training data set to train a first model of the neural network;
- filtering a second subset of the labeled training data set using the first model to provide a first model-filtered subset of the second subset;
- using the first model-filtered subset of the second subset to train a first refined model of the neural network;
- filtering the first subset using the first refined model to provide a first refined model-filtered subset of the first subset;
- using the first refined model-filtered subset of the first subset to train a second refined model of the neural network;
- and
- filtering the second subset of the labeled training data set using the second refined model to provide a second refined model-filtered subset of the second subset.
A computer system configured to clean training data for a neural network, comprising:
- one or more processors and memory storing computer program instructions configured to execute a process comprising:
- accessing a labeled training data set;
- using a first subset of the labeled training data set to train a first model of the neural network;
- filtering a second subset of the labeled training data set using the first model to provide a first model-filtered subset of the second subset;
- using the first model-filtered subset of the second subset to train a first refined model of the neural network;
- filtering the first subset using the first refined model to provide a first refined model-filtered subset of the first subset;
- using the first refined model-filtered subset of the first subset to train a second refined model of the neural network;
- and
- filtering the second subset of the labeled training data set using the second refined model to provide a second refined model-filtered subset of the second subset.
A computer program product configured to support cleaning training data for a neural network, comprising a non-transitory computer readable memory storing computer program instructions configured to execute a process comprising:
- accessing a labeled training data set;
- using a first subset of the labeled training data set to train a first model of the neural network;
- filtering a second subset of the labeled training data set using the first model to provide a first model-filtered subset of the second subset;
- using the first model-filtered subset of the second subset to train a first refined model of the neural network;
- filtering the first subset using the first refined model to provide a first refined model-filtered subset of the first subset;
- using the first refined model-filtered subset of the first subset to train a second refined model of the neural network;
- and
- filtering second subset of the labeled training data set using the second refined model to provide a second refined model-filtered subset of the second subset.
Dependencies are inferred from the claim text.