
# Modified Victorian Era Authorship Attribution Dataset

## About

This data set is a modified version of the one that can be found [here](https://archive.ics.uci.edu/ml/datasets/Victorian+Era+Authorship+Attribution).

The difference being that the training dataset was split into two parts: 80% training, 20% testing with labels. 
Splitting was done with a random stratified sample approach.
This is different than the source dataset which did not have any labels for the testing data.

Additionally, all text has been converted to UTF-8 format and any errors were ignored.

The original testing data is not included with this release.

## Citation

> GUNGOR, ABDULMECIT, Benchmarking Authorship Attribution Techniques Using Over A Thousand Books by Fifty Victorian Era Novelists, Purdue Master of Thesis, 2018-04
task_categories:text-classification size_categories:10K<n<100K language:en license:agpl-3.0 region:us
{"language": ["en"], "license": "agpl-3.0", "size_categories": ["10K<n<100K"], "task_categories": ["text-classification"]}
TAGS
#task_categories-text-classification #size_categories-10K<n<100K #language-English #license-agpl-3.0 #region-us 


# Modified Victorian Era Authorship Attribution Dataset

## About

This data set is a modified version of the one that can be found here.

The difference being that the training dataset was split into two parts: 80% training, 20% testing with labels. 
Splitting was done with a random stratified sample approach.
This is different than the source dataset which did not have any labels for the testing data.

Additionally, all text has been converted to UTF-8 format and any errors were ignored.

The original testing data is not included with this release.

> GUNGOR, ABDULMECIT, Benchmarking Authorship Attribution Techniques Using Over A Thousand Books by Fifty Victorian Era Novelists, Purdue Master of Thesis, 2018-04
# Modified Victorian Era Authorship Attribution Dataset ## About

This data set is a modified version of the one that can be found here.

The difference being that the training dataset was split into two parts: 80% training, 20% testing with labels. 
Splitting was done with a random stratified sample approach.
This is different than the source dataset which did not have any labels for the testing data.

Additionally, all text has been converted to UTF-8 format and any errors were ignored.

The original testing data is not included with this release.

> GUNGOR, ABDULMECIT, Benchmarking Authorship Attribution Techniques Using Over A Thousand Books by Fifty Victorian Era Novelists, Purdue Master of Thesis, 2018-04
TAGS
#task_categories-text-classification #size_categories-10K<n<100K #language-English #license-agpl-3.0 #region-us 
 # Modified Victorian Era Authorship Attribution Dataset ## About

This data set is a modified version of the one that can be found here.

The difference being that the training dataset was split into two parts: 80% training, 20% testing with labels. 
Splitting was done with a random stratified sample approach.
This is different than the source dataset which did not have any labels for the testing data.

Additionally, all text has been converted to UTF-8 format and any errors were ignored.

The original testing data is not included with this release.

> GUNGOR, ABDULMECIT, Benchmarking Authorship Attribution Techniques Using Over A Thousand Books by Fifty Victorian Era Novelists, Purdue Master of Thesis, 2018-04
passage: TAGS
#task_categories-text-classification #size_categories-10K<n<100K #language-English #license-agpl-3.0 #region-us 
# Modified Victorian Era Authorship Attribution Dataset## About

This data set is a modified version of the one that can be found here.

The difference being that the training dataset was split into two parts: 80% training, 20% testing with labels. 
Splitting was done with a random stratified sample approach.
This is different than the source dataset which did not have any labels for the testing data.

Additionally, all text has been converted to UTF-8 format and any errors were ignored.

The original testing data is not included with this release.

> GUNGOR, ABDULMECIT, Benchmarking Authorship Attribution Techniques Using Over A Thousand Books by Fifty Victorian Era Novelists, Purdue Master of Thesis, 2018-04