Background: Recurrence is an important cornerstone in breast cancer behavior, intrinsically
related to mortality. In spite of its relevance, it is rarely recorded in the majority of breast …

The past decade has seen a significant interest on the problem of inducing decision trees
that take account of costs of misclassification and costs of acquiring the features used for …

Abstract KNN (K Nearest Neighbors) classification is one of top-10 data mining algorithms. It
is significant to extend KNN classifiers sensitive to costs for imbalanced data classification …

Existing kNN imputation methods for dealing with missing data are designed according to
Minkowski distance or its variants, and have been shown to be generally efficient for …

Missing data imputation is a key issue in learning from incomplete data. Various techniques
have been developed with great successes on dealing with missing values in data sets with …

This paper presents a particle swarm optimization (PSO)-based fuzzy expert system for the
diagnosis of coronary artery disease (CAD). The designed system is based on the …

Cost-sensitive learning is an aspect of algorithm-level modifications for class imbalance.
Here, instead of using a standard error-driven evaluation (or 0–1 loss function), a …

In linguistics, the uncertainty of context due to polysemy is widespread, which attracts much
attention. Quantum-inspired complex word embedding based on Hilbert space plays an …

In this paper, we review recent progresses in the area of mining data from multiple data
sources. The advancement of information communication technology has generated a large …

Different from previous imputation methods which impute missing values in the incomplete
samples by using the information in the complete samples, this paper proposes a Date-drive …