Data Science and Classification. Springer, 2006.in H.-H. Bock, V. Batagelj, A. Ferligoj and A. Ziberna (eds), Data Science and Classification. Heidelberg: Springer. pp. 119-30.Batagelj V, Bock H, Ferligoj A. "D
Many traditional and recent resampling methods only aim at getting a more balanced version of the training data and do not factor in the problem of class overlap [11], [12], [13]. Some methods deal with instances in the overlapping region, especially those near the borderline areas; however...
The choice of classification algorithm requires considering multiple aspects of the problem: type of data, statistical distribution of classes, target accuracy, ease of use, speed, scalability, and interpretability of the classifier. Direct tradeoffs of some of these factors exist, and it is also im...
Another problem is that a unifying definition of neuronal type should involve all three categories of properties, namely, physiological, morphological and molecular, which implies that they co-vary. Although such a satisfying correspondence has been shown for some types (see below), it seems unlikely...
THE relations of bibliography to science with especial regard to classification, as brought forward in Dr. S. C. Bradford's recent articles in NATURE,1 have for many years been my purposive study. I welcome the renewed and increasing interest in the problems involved. It is very regrettable,...
Data series classification is an important and challenging problem in data science. Explaining the classification decisions by finding the discriminant parts of the input that led the algorithm to some decision is a real need in many applications. Convolutional neural networks perform well for the ...
Time Series Classification (TSC) is an important and challenging problem in data mining. With the increase of time series data availability, hundreds of TS
uses the updating approach of weights. Faults are also propagated backward using this method. This method is constrained by local minima solutions. This study solves the problem by employing an effective modified technique that improves accuracy and is used in a variety of future prediction ...
volumes swelling, these processes are no longer viable.Proofpoint Intelligent Classification and Protection(PCIP) can help organisations modernise and enhance theirdata security. The solution uses advanced artificial intelligence (AI)-based technologies to help solve the problem of modern data secu...
problem is shown.Diagonal elementsof the inner 3×3 table are percentages of correct classifications. The sum of each row is a prior probability of the respective class, and the sum of each column is the percentage of all examples that were classified in the respective class. The difference ...