Machine Learning for Data Science Handbook

Edited by Lior Rokach (), Oded Maimon () and Erez Shmueli ()

in Springer Books from Springer

Date: 2023
Edition: Third Edition 2023
ISBN: 978-3-031-24628-9
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Chapters in this book:

Data Science and Knowledge Discovery Using Machine Learning Methods

Oded Maimon, Lior Rokach and Erez Shmueli

Handling Missing Attribute Values

Jerzy W. Grzymala-Busse and Witold J. Grzymala-Busse

Data Integration Process Automation Using Machine Learning: Issues and Solution

Kartick Chandra Mondal and Swati Saha

Rule Induction

Jerzy W. Grzymala-Busse

Nearest-Neighbor Methods: A Modern Perspective

Aryeh Kontorovich and Samory Kpotufe

Support Vector Machines

Armin Shmilovici

Empowering Interpretable, Explainable Machine Learning Using Bayesian Network Classifiers

Boaz Lerner

Soft Decision Trees

Oren Fivel, Moshe Klein and Oded Maimon

Quality Assessment and Evaluation Criteria in Supervised Learning

Amichai Painsky

Trajectory Clustering Analysis

Yulong Wang and Yuan Yan Tang

Clustering High-Dimensional Data

Michael E. Houle, Marie Kiermeier and Arthur Zimek

Fuzzy C-Means Clustering: Advances and Challenges (Part II)

Janmenjoy Nayak, H. Swapna Rekha and Bighnaraj Naik

Clustering in Streams

Charu C. Aggarwal

Introduction to Deep Learning

Lihi Shiloh-Perl and Raja Giryes

Graph Embedding

Palash Goyal

Autoencoders

Dor Bank, Noam Koenigstein and Raja Giryes

Generative Adversarial Networks

Gilad Cohen and Raja Giryes

Spatial Data Science

Yan Li, Yiqun Xie and Shashi Shekhar

Multimedia Data Learning

Zhongfei Mark Zhang and Ruofei Bruce Zhang

Web Mining

Petar Ristoski

Mining Temporal Data

Robert Moskovitch

Cloud Big Data Mining and Analytics: Bringing Greenness and Acceleration in the Cloud

Hrishav Bakul Barua and Kartick Chandra Mondal

Multi-Label Ranking: Mining Multi-Label and Label Ranking Data

Lihi Dery

Reinforcement Learning for Data Science

Jonatan Barkan, Michal Moran and Goren Gordon

Adversarial Machine Learning

Ziv Katzir and Yuval Elovici

Ensembled Transferred Embeddings

Yonatan Hadar and Erez Shmueli

Data Mining in Medicine

Beatrice Amico, Carlo Combi and Yuval Shahar

Recommender Systems

Shuai Zhang, Aston Zhang and Lina Yao

Activity Recognition

Jindong Wang, Yiqiang Chen and Chunyu Hu

Social Network Analysis for Disinformation Detection

Aviad Elyashar, Maor Reuben, Asaf Shabtai and Rami Puzis

Online Propaganda Detection

Mark Last

Interpretable Machine Learning forFinancial Applications

Boris Kovalerchuk, Evgenii Vityaev, Alexander Demin and Antoni Wilinski

Predictive Analytics for Targeting Decisions

Jacob Zahavi

Machine Learning for the Geosciences

Neta Rabin and Yuri Bregman

Sentiment Analysis for Social Text

Nir Ofek

Human Resources-Based Organizational Data Mining (HRODM): Themes, Trends, Focus, Future

Hila Chalutz-Ben Gal

Algorithmic Fairness

Dana Pessach and Erez Shmueli

Privacy-Preserving Data Mining (PPDM)

Ron S. Hirschprung

Explainable Machine Learning and Visual Knowledge Discovery

Boris Kovalerchuk

Visual Analytics and Human Involvement in Machine Learning

Salomon Eisler and Joachim Meyer

Explainable Artificial Intelligence (XAI): Motivation, Terminology, and Taxonomy

Aviv Notovich, Hila Chalutz-Ben Gal and Irad Ben-Gal

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DOI: 10.1007/978-3-031-24628-9

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