Real-world data is never perfect and can often suffer from corruptions (noise) that may impact interpretations of the data, models created from the data and decisions made based on...
Analyzing the quality of data prior to constructing data mining models is emerging as an important issue. Algorithms for identifying noise in a given data set can provide a good me...
Jason Van Hulse, Taghi M. Khoshgoftaar, Haiying Hu...
We study the problem of PAC-learning Boolean functions with random attribute noise under the uniform distribution. We define a noisy distance measure for function classes and sho...
Nader H. Bshouty, Jeffrey C. Jackson, Christino Ta...
Attribute noise can affect classification learning. Previous work in handling attribute noise has focused on those predictable attributes that can be predicted by the class and o...
This paper presents a detailed comparative study of 4 rotation invariant texture analysis methods. Human subjects are included as a benchmark for the computational methods. Experi...