Machine learning for data science handbook : data mining and knowledge discovery handbook / Lior Rokach, Oded Maimon, Erez Shmueli, editors.

Introduction to Knowledge Discovery and Data Mining
Preprocessing Methods
Data Cleansing: A Prelude to Knowledge Discovery
Handling Missing Attribute Values
Geometric Methods for Feature Extraction and Dimensional Reduction - A Guided Tour
Dimension Reduction and Feature Selection
Discretization Methods
Outlier Detection
Supervised Methods
Supervised Learning
Classification Trees
Bayesian Networks
Data Mining within a Regression Framework
Support Vector Machines
Rule Induction
Unsupervised Methods
A survey of Clustering Algorithms
Association Rules
Frequent Set Mining
Constraint-based Data Mining
Link Analysis
Soft Computing Methods
A Review of Evolutionary Algorithms for Data Mining
A Review of Reinforcement Learning Methods
Neural Networks For Data Mining
Granular Computing and Rough Sets - An Incremental Development
Pattern Clustering Using a Swarm Intelligence Approach
Using Fuzzy Logic in Data Mining
Supporting Methods
Statistical Methods for Data Mining
Logics for Data Mining
Wavelet Methods in Data Mining
Fractal Mining - Self Similarity-based Clustering and its Applications
Visual Analysis of Sequences Using Fractal Geometry
Interestingness Measures - On Determining What Is Interesting
Quality Assessment Approaches in Data Mining
Data Mining Model Comparison
Data Mining Query Languages
Advanced Methods
Mining Multi-label Data
Privacy in Data Mining
Meta-Learning - Concepts and Techniques
Bias vs Variance Decomposition for Regression and Classification
Mining with Rare Cases
Data Stream Mining
Mining Concept-Drifting Data Streams
Mining High-Dimensional Data
Text Mining and Information Extraction
Spatial Data Mining
Spatio-temporal clustering
Data Mining for Imbalanced Datasets: An Overview
Relational Data Mining
Web Mining
A Review of Web Document Clustering Approaches
Causal Discovery
Ensemble Methods in Supervised Learning
Data Mining using Decomposition Methods
Information Fusion - Methods and Aggregation Operators
Parallel and Grid-Based Data Mining Algorithms, Models and Systems for High-Performance KDD
Collaborative Data Mining
Organizational Data Mining
Mining Time Series Data
Applications
Multimedia Data Mining
Data Mining in Medicine
Learning Information Patterns in Biological Databases - Stochastic Data Mining
Data Mining for Financial Applications
Data Mining for Intrusion Detection
Data Mining for CRM
Data Mining for Target Marketing
NHECD - Nano Health and Environmental Commented Database
Software
Commercial Data Mining Software
Weka-A Machine Learning Workbench for Data Mining.