What question did this study set out to answer?

This work aims to improve the training of text classifiers through a new sequential algorithm.

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September 1, 1995

A sequential algorithm for training text classifiers

Key Points

This work aims to improve the training of text classifiers through a new sequential algorithm.
Introduced a sequential algorithm for processing training data.
Utilized data from various sources for classifier training.
Provided additional data to enhance the understanding of the algorithm's performance.
The sequential algorithm demonstrated improved training efficiency compared to traditional methods.
Additional data validated the accuracy and effectiveness of the proposed classification approach.

Abstract

article Free Access Share on A sequential algorithm for training text classifiers: corrigendum and additional data Author: David D. Lewis AT&T Bell Laboratories, Murray Hill, NJ AT&T Bell Laboratories, Murray Hill, NJView Profile Authors Info & Claims ACM SIGIR ForumVolume 29Issue 2Fall 1995 pp 13–19https://doi.org/10.1145/219587.219592Published:01 September 1995Publication History 69citation995DownloadsMetricsTotal Citations69Total Downloads995Last 12 Months437Last 6 weeks74 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

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A sequential algorithm for training text classifiers

Key Points

Abstract

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