Datasets:
Commit
•
38e9858
1
Parent(s):
bc0e6c5
Delete sms/README.md
Browse files- sms/README.md +0 -18
sms/README.md
DELETED
|
@@ -1,18 +0,0 @@
|
|
| 1 |
-
# SMS
|
| 2 |
-
|
| 3 |
-
This dataset was created from the SMS Spam Collection and SMS Phishing Dataset for Machine Learning and Pattern Recognition, which contained 5,574 and 5,971 real English SMS messages, respectively. As these two datasets overlap, after de-duplication, the final dataset is made up of 6574 texts released by a private UK-based wireless operator; 1274 of them are deceptive, and the remaining 5300 are not.
|
| 4 |
-
|
| 5 |
-
## Cleaning
|
| 6 |
-
|
| 7 |
-
Each dataset has been cleaned using Cleanlab. Non-english entries, erroneous (parser error) entries, empty entries, duplicate entries, entries of length less than 2 characters or exceeding 1000000 characters were all removed.
|
| 8 |
-
|
| 9 |
-
## Preprocessing
|
| 10 |
-
|
| 11 |
-
Whitespace, quotes, bulletpoints, unicode is normalized.
|
| 12 |
-
|
| 13 |
-
## Data
|
| 14 |
-
|
| 15 |
-
The dataset consists of "text" (string) and "is_deceptive" (1,0). 1 means the text is deceptive, 0 indicates otherwise.
|
| 16 |
-
|
| 17 |
-
There are 6574 samples in the dataset, contained in `sms.jsonl`. For reproduceability, the data is also split into training, test, and validation sets in 80/10/10 ratio. They are named `train.jsonl`, `test.jsonl`, `valid.jsonl`. The sampling process was stratified. The training set contains 5259 samples, the validation and the test sets have 657 and 658 samles, respectively.
|
| 18 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|