£180.72

Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance

AI & Machine Learning

Price data last checked 83 day(s) ago - refreshing...

View at Amazon

Price History & Forecast

Last 8 days • 8 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 8 days • 1 price levels

Days at Price

Price Analysis

Most common price: £181 (8 days, 100.0%)

Price range: £181 - £181

Price levels: 1 different prices over 8 days

Description

Over the last two decades, researchers are looking at imbalanced data learning as a prominent research area. Many critical real-world application areas like finance, health, network, news, online advertisement, social network media, and weather have imbalanced data, which emphasizes the research necessity for real-time implications of precise fraud/defaulter detection, rare disease/reaction prediction, network intrusion detection, fake news detection, fraud advertisement detection, cyber bullying identification, disaster events prediction, and more. Machine learning algorithms are based on the heuristic of equally-distributed balanced data and provide the biased result towards the majority data class, which is not acceptable considering imbalanced data is omnipresent in real-life scenarios and is forcing us to learn from imbalanced data for foolproof application design. Imbalanced data is multifaceted and demands a new perception using the novelty at sampling approach of data preprocessing, an active learning approach, and a cost perceptive approach to resolve data imbalance. Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance offers new aspects for imbalanced data learning by providing the advancements of the traditional methods, with respect to big data, through case studies and research from experts in academia, engineering, and industry. The chapters provide theoretical frameworks and the latest empirical research findings that help to improve the understanding of the impact of imbalanced data and its resolving techniques based on data preprocessing, active learning, and cost perceptive approaches. This book is ideal for data scientists, data analysts, engineers, practitioners, researchers, academicians, and students looking for more information on imbalanced data characteristics and solutions using varied approaches.

Product Specifications

Format: paperback
ASIN: 1799873722
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 04 June 2021
Listed Since: 09 December 2020

Barcode

No barcode data available

Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Handbook of Research on Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance (Advances in Data Mining and Database Management)

Learning from Imbalanced Data Sets

Fundamentals of Data Science: Theory and Practice

The Beginner's Guide to Data Science

Data Science and Predictive Analytics: Biomedical and Health Applications using R (The Springer Series in Applied Machine Learning)

Data Science and Predictive Analytics: Biomedical and Health Applications using R (The Springer Series in Applied Machine Learning)

Applied Machine Learning for Data Science Practitioners

Machine Learning and Big Data: Concepts, Algorithms, Tools and Applications

John Wiley & Sons Data Mining and Machine Learning Applications

Intelligent Data Analytics for Terror Threat Prediction: Architectures, Methodologies, Techniques, and Applications

Practical Machine Learning for Data Analysis Using Python

Applying Data Science and Learning Analytics Throughout a Learner’s Lifespan

Advances in Data Science: Methodologies and Applications: 189 (Intelligent Systems Reference Library, 189)

Intelligent Techniques for Predictive Data Analytics

Data Science Handbook: A Practical Approach

Springer - Dirty Data Processing for Machine Learning Book

Statistical Learning and Data Science (Computer Science and Data Analysis)

A Closer Look at Big Data Analytics (Computer Science, Technology and Applications)

Algorithms for Data Science

Applications of AI for Interdisciplinary Research

Learning Representation for Multi-View Data Analysis: Models and Applications (Advanced Information and Knowledge Processing)

Fundamentals and Methods of Machine and Deep Learning: Algorithms, Tools, and Applications

Machine Learning for Healthcare Applications

The Data Science Manual: A Comprehensive Guide to Tools and Techniques for Data Analysis, Modeling, and Deployment with Python