Amazon Comprehend Now Supports Confusion Matrices for Custom Classification
Amazon Comprehend helps you solve a variety of use cases with custom classification. For example, you can build classifiers to organize your daily customer feedback into categories like “loyalty”, “sales” or “product defect”. Amazon Comprehend removes the complexity to create custom classification models, requiring only a CSV file with labels and example text.
A confusion matrix helps you understand how your labels are performing based on the training data you provided. For example, if you have two labels with similar training content, the custom classification model may not be able to clearly distinguish between these labels. Using the confusion matrix, you can focus on creating better training content, so each label is more distinct from the other.
Get started with Amazon Comprehend custom classification models here and learn more about how to use a confusion matrix as part of training your model here.
Amazon Comprehend helps you solve a variety of use cases with custom classification. For example, you can build classifiers to organize your daily customer feedback into categories like “loyalty”, “sales” or “product defect”. Amazon Comprehend removes the complexity to create custom classification models, requiring only a CSV file with labels and example text.
A confusion matrix helps you understand how your labels are performing based on the training data you provided. For example, if you have two labels with similar training content, the custom classification model may not be able to clearly distinguish between these labels. Using the confusion matrix, you can focus on creating better training content, so each label is more distinct from the other.
Get started with Amazon Comprehend custom classification models here and learn more about how to use a confusion matrix as part of training your model here.