Semi-supervised learning methods are usually employed in the classification of data sets where only a small subset of the data items is labeled. In these scenarios, label noise is a crucial issue, since the noise may easily ...

Noisy data are common in real-world problems and may have several causes, like in accuracies, distortions or contamination during data collection, storage and/or transmission. The presence of noise in data can affect the ...

Noisy data are common in real-World problems and may have several causes, like inaccuracies, distortions or contamination during data collection, storage and/or transmission. the presence of noise in data can affect the ...

Face annotation is a naming procedure that assigns the correct name to a person emerging from an image. Faces that are manually annotated by people in online applications include incorrect labels, giving rise to the issue ...

Noise filtering can be considered an important preprocessing step in the data mining process, making data more reliable for pattern extraction. An interesting aspect for increasing data understanding would be to rank the ...

In Data Mining, the value of extracted knowledge is directly related to the quality of the used data. This makes data preprocessing one of the most important steps in the knowledge discovery process. A common problem ...

In the field of network security, the process of labeling a network traffic dataset is specially expensive since expert knowledge is required to perform the annotations. With the aid of visual analytic applications such ...