Structured Data Autolabeling
1. What is Structured Data Autolabeling?
Structured classification, regularization regression (continuous value), manual labeling of natural language data, and autolabeling are available.
Labeling AI is available for both data containing and data containing results.
Data without results: Load data → Manual labeling → Create customai → Auto labeling
Data with results : Load data → Create customai → Add data (data before labeling) → Auto-labeling
Data with and without results: Load data → Create customai → Auto-labeling
For data that does not contain the results, you can proceed with autolabeling by generating customai after proceeding with a small amount of manual labeling.
For data containing the results, auto-labeling can proceed immediately after creating customai and adding unlabeled data.
2. Create Structured Data Autolabeling
[NOTE] In this case, describe how to creat project using data without result.
1) Upload data
1-1) Click LABELING AI's Start Label button to go to DS2 DATASET.
1-2) Select the desired dataset from the data list, or click Add Data to upload the file you want to label.
1-3) Select the CSV file format.
- If the upload data contains a column of results
If the upload data contains a column of results
- If the upload data doesn't contain a column of results
Under Data Settings, select the 'Enter column name directly' option, enter the column name you want to label, and click OK.
2) Create project
2-1) After selecting a project name, description, and category, click Next to complete the project creation.
2-2) Click the Create Project button to go to the Project Management window you created, and click "Labeling AI | Labeling" to confirm that the project list has been updated.
3) Enter a class
3-1) If the dashboard "classification" is empty, you must add the class. Click "More" in the classification or "Class" in the middle.
3-2) Click the Add + Class button to add the class name you want to label.
3-3) Sets the class name and color. Class names must be written in English, and only some special characters are available. After completion, click the Done button.
4) Manual labeling
You can generate Custom AI by performing more than 10 manual labeling for each class of categorized and natural language processing data, and a total of 10 manual labeling for continuous value data.
4-1) When class creation for 'Classification' is complete, click the Start Manual Labeling button to the right of the project name to start manual labelling.
4-2) If you select and click on a class at the bottom of the screen that matches the data information, the selected class is set in the rightmost column of the data information. After confirmation, click the Save and Next buttons to proceed with labeling.
If you select and click on a class at the bottom of the screen that matches the data information, the selected class is set in the rightmost column of the data information. After confirmation, click the Save and Next buttons to proceed with labeling.
5) Custom AI
5-1) When you have more than 10 objects per class, click the Create CUSTOM AI button to create artificial intelligence for auto-labeling.
5-2) Select the class you want to label and click Start AI Development.
5-3) Pop-up of AI development start appears. The beginning and end of modeling learning can be found through email and notification history.
6) Start Auto-labeling
6-1) Add the data you want to auto-labeled. (If unlabeled data has already been uploaded, you can auto-labeled without any additional data.)
6-2) Click the Start Autolabeling button to start autolabeling.
6-3) Starting and ending auto-labeling can be found in your email and notification history.
2-7. Inspection and Labeling AI Advancement
1) You can verify that auto-labeled data is properly labeled, and correct mislabeled data.
2) Also, by regenerating CUSTOM AI with modified label data, you can upgrade it to a more accurate autolabeling model.