Learning from Imbalanced Data Sets (Hardcover, 2018)

1 Introduction to KDD and Data Science.- 2 Foundations on Imbalanced Classification.- 3 Performance measures.- 4 Cost-sensitive Learning.- 5 Data Level Preprocessing Methods.- 6 Algorithm-level Approaches.- 7 Ensemble Learning.- 8 Imbalanced Classification with Multiple Classes.- 9 Dimensionality Reduction for Imbalanced Learning.- 10 Data Intrinsic Characteristics.- 11 Learning from Imbalanced Data Streams.- 12 Non-Classical Imbalanced Classification Problems.- 13 Imbalanced Classification for Big Data.- 14 Software and Libraries for Imbalanced Classification.