Data Analysis, Machine Learning and Knowledge Discovery

✍ Scribed by Myra Spiliopoulou, Lars Schmidt-Thieme, Ruth Janning

Publisher: Springer
Year: 2013
Tongue: English
Leaves: 462
Series: Studies in Classification, Data Analysis, and Knowledge Organization
Edition: 2014
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Focus on the commonalities concerning data analysis in computer science and in statistics
Emphasis on both methods (statistical analysis and machine learning) and applications (marketing, finance, bioinformatics, musicology, psychology)
Presentation of general methods and techniques that can be applied to a variety of fields

Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medicine, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and knowledge discovery presented during the 36th annual conference of the German Classification Society (GfKl). The conference was held at the University of Hildesheim (Germany) in August 2012.

Content Level » Research

Keywords » Applied Statistics - Classification - Clustering - Data Analysis - Prediction

Related subjects » Computational Statistics - Database Management & Information Retrieval - Finance & Banking - Marketing - Psychology

📜 SIMILAR VOLUMES

Data Analysis, Machine Learning and Know

📁 Data Analysis, Machine Learning and Knowledge Discovery

✍ Udo Bankhofer, Dieter William Joenssen (auth.), Myra Spiliopoulou, Lars Schmidt- 📂 Library 📅 2014 🏛 Springer International Publishing 🌐 English

Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketi

Knowledge-Guided Machine Learning: Accel

📁 Knowledge-Guided Machine Learning: Accelerating Discovery Using Scientific Knowledge and Data (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

✍ Anuj Karpatne (editor), Ramakrishnan Kannan (editor), Vipin Kumar (editor) 📂 Library 📅 2022 🏛 Chapman and Hall/CRC 🌐 English

Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the prese

Machine Learning for Data Science Handbo

📁 Machine Learning for Data Science Handbook : Data Mining and Knowledge Discovery Handbook

✍ Lior Rokach; Oded Maimon; Erez Shmueli 📂 Library 📅 2023 🏛 Springer International Publishing 🌐 English

This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions

Machine Learning for Data Science Handbo

📁 Machine Learning for Data Science Handbook: Data Mining and Knowledge Discovery Handbook

✍ Lior Rokach (editor), Oded Maimon (editor), Erez Shmueli (editor) 📂 Library 📅 2023 🏛 Springer 🌐 English

This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the ex

Visual Knowledge Discovery and Machine L

📁 Visual Knowledge Discovery and Machine Learning

✍ Boris Kovalerchuk 📂 Library 📅 2018 🏛 Springer 🌐 English

Visual Knowledge Discovery and Machine L

📁 Visual Knowledge Discovery and Machine Learning

✍ Boris Kovalerchuk (auth.) 📂 Library 📅 2018 🏛 Springer International Publishing 🌐 English

This book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns. It vastly expands the class of reversible lossless 2-D and 3-D visualization methods, which preserve the n-D information. This class of visual