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Eric Ed585216%3a Comparing Machine Learning Classification Approaches For Predicting Expository Text Difficulty by Eric
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1ERIC ED585216: Comparing Machine Learning Classification Approaches For Predicting Expository Text Difficulty
By ERIC
While hierarchical machine learning approaches have been used to classify texts into different content areas, this approach has, to our knowledge, not been used in the automated assessment of text difficulty. This study compared the accuracy of four classification machine learning approaches (flat, one-vs-one, one-vs-all, and hierarchical) using natural language processing features in predicting human ratings of text difficulty for two sets of texts. The hierarchical classification was the most accurate for the two text sets considered individually (Set A, 77.78%; Set B, 82.05%), while the non-hierarchical approaches, one-vs-one and one-vs-all, performed similar to the hierarchical classification for the combined set (71.43%). These findings suggest both promise and limitations for applying hierarchical approaches to text difficulty classification. It may be beneficial to apply a recursive top-down approach to discriminate the subsets of classes that are at the top of the hierarchy and less related, and then further separate the classes into subsets that may be more similar to one other. These results also suggest that a single approach may not always work for all types of datasets and that it is important to evaluate which machine learning approach and algorithm works best for particular datasets. The authors encourage more work in this area to help suggest which types of algorithms work best as a function of the type of dataset.
“ERIC ED585216: Comparing Machine Learning Classification Approaches For Predicting Expository Text Difficulty” Metadata:
- Title: ➤ ERIC ED585216: Comparing Machine Learning Classification Approaches For Predicting Expository Text Difficulty
- Author: ERIC
- Language: English
“ERIC ED585216: Comparing Machine Learning Classification Approaches For Predicting Expository Text Difficulty” Subjects and Themes:
- Subjects: ➤ ERIC Archive - ERIC - Balyan, Renu McCarthy, Kathryn S. McNamara, Danielle S. Artificial Intelligence - Classification - Comparative Analysis - Prediction - Accuracy - Natural Language Processing - Readability - Expository Writing - Readability Formulas
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- Internet Archive ID: ERIC_ED585216
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The book is available for download in "texts" format, the size of the file-s is: 5.95 Mbs, the file-s for this book were downloaded 26 times, the file-s went public at Thu May 25 2023.
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1Boy Crusoe
By Allan Eric

Also published as" A Yankee Crusoe" . A 15 year old hard working and studious farm boy finds the lure of adventure on the seas as a merchant seaman more than he can resist. This is his story. " I was born in a little town in the State of Maine, near the close of the Civil War. My boyhood life did not differ materially from that of the average farmer's son in the remote country districts of New England--except, perhaps, that I read more and thought more. Hard work on the rugged soil, two terms each year in the little yellow country schoolhouse, a day's fishing now and then filled the early years of my life full to over-flowing. " What he gets is enough excitement and adventure to overflow his wildest dreams. How he experiences disaster and uses his wits and knowledge to overcome every problem makes for a great read. - Summary by Phil Chenevert
“Boy Crusoe” Metadata:
- Title: Boy Crusoe
- Author: Allan Eric
- Language: English
- Publish Date: 1910
Edition Specifications:
- Format: Audio
- Number of Sections: 23
- Total Time: 03:45:08
Edition Identifiers:
- libriVox ID: 8827
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- File Name: aboycrusoe_1408_librivox
- File Format: zip
- Total Time: 03:45:08
- Download Link: Download link
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