Datasets:
Requesting clarification on the meaning of labels in the dataset
Dear Author,
I am currently working with your dataset and have a question regarding the labels. In the readme file, it's mentioned that each sample has a label sequence of 3 float32 values. However, the specific meaning of these labels is not clear.
Could you please provide more information on what these three label values represent? Specifically:
What do the three positions in the label sequence [x, y, z] correspond to?
Is this a multi-label classification task, where each position represents a distinct category or feature?
If so, what are the names or descriptions of these three categories/features?
Does a value of 1.0 indicate the presence of a feature and 0.0 its absence?
Are there cases where values other than 0.0 and 1.0 appear, and if so, what do they signify?
Any additional context or explanation you can provide about the labeling scheme would be greatly appreciated. This information will be crucial for properly understanding and utilizing the dataset.
Thank you for your time and assistance.
Hello, thank you for your interest in this dataset.
- The dataset has three features; "Crack", "Red-Dots" and "Toothmark", which are binary encoded. For example, an image with the label [1, 0, 0] is positive for "Crack", and negative for "Red-Dots" and "Toothmark".
- Yes, this a multi-label classification task.
- The names are "Crack", "Red-Dots" and "Toothmark".
- Yes, 1.0 indicates a positive label while 0 indicates a negative label. Labels are either 0 or 1.
I hope this answers your questions!