Xgboost The Extreme Gradient Boosting For Mining Applications
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Xgboost The Extreme Gradient Boosting For Mining Applications
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Author : Nonita Sharma
language : en
Publisher: GRIN Verlag
Release Date : 2018-03-13
Xgboost The Extreme Gradient Boosting For Mining Applications written by Nonita Sharma and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-13 with Computers categories.
Technical Report from the year 2017 in the subject Computer Science - Internet, New Technologies, grade: 8, , language: English, abstract: Tree boosting has empirically proven to be a highly effective and versatile approach for data-driven modelling. The core argument is that tree boosting can adaptively determine the local neighbourhoods of the model thereby taking the bias-variance trade-off into consideration during model fitting. Recently, a tree boosting method known as XGBoost has gained popularity by providing higher accuracy. XGBoost further introduces some improvements which allow it to deal with the bias-variance trade-off even more carefully. In this research work, we propose to demonstrate the use of an adaptive procedure i.e. Learned Loss (LL) to update the loss function as the boosting proceeds. Accuracy of the proposed algorithm i.e. XGBoost with Learned Loss boosting function is evaluated using test/train method, K-fold cross validation, and Stratified cross validation method and compared with the state of the art algorithms viz. XGBoost, AdaBoost, AdaBoost-NN, Linear Regression(LR),Neural Network(NN), Decision Tree(DT), Support Vector Machine(SVM), bagging-DT, bagging-NN and Random Forest algorithms. The parameters evaluated are accuracy, Type 1 error and Type 2 error (in Percentages). This study uses total ten years of historical data from Jan 2007 to Aug 2017 of two stock market indices CNX Nifty and S&P BSE Sensex which are highly voluminous. Further, in this research work, we will investigate how XGBoost differs from the more traditional ensemble techniques. Moreover, we will discuss the regularization techniques that these methods offer and the effect these have on the models. In addition to this, we will attempt to answer the question of why XGBoost seems to win so many competitions. To do this, we will provide some arguments for why tree boosting, and in particular XGBoost, seems to be such a highly effective and versatile approach to predictive modelling. The core argument is that tree boosting can be seen to adaptively determine the local neighbourhoods of the model. Tree boosting can thus be seen to take the bias-variance trade off into consideration during model fitting. XGBoost further introduces some improvements which allow it to deal with the bias-variance trade off even more carefully.
Hands On Gradient Boosting With Xgboost And Scikit Learn
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Author : Corey Wade
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-10-16
Hands On Gradient Boosting With Xgboost And Scikit Learn written by Corey Wade and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-16 with Computers categories.
Get to grips with building robust XGBoost models using Python and scikit-learn for deployment Key Features Get up and running with machine learning and understand how to boost models with XGBoost in no time Build real-world machine learning pipelines and fine-tune hyperparameters to achieve optimal results Discover tips and tricks and gain innovative insights from XGBoost Kaggle winners Book Description XGBoost is an industry-proven, open-source software library that provides a gradient boosting framework for scaling billions of data points quickly and efficiently. The book introduces machine learning and XGBoost in scikit-learn before building up to the theory behind gradient boosting. You'll cover decision trees and analyze bagging in the machine learning context, learning hyperparameters that extend to XGBoost along the way. You'll build gradient boosting models from scratch and extend gradient boosting to big data while recognizing speed limitations using timers. Details in XGBoost are explored with a focus on speed enhancements and deriving parameters mathematically. With the help of detailed case studies, you'll practice building and fine-tuning XGBoost classifiers and regressors using scikit-learn and the original Python API. You'll leverage XGBoost hyperparameters to improve scores, correct missing values, scale imbalanced datasets, and fine-tune alternative base learners. Finally, you'll apply advanced XGBoost techniques like building non-correlated ensembles, stacking models, and preparing models for industry deployment using sparse matrices, customized transformers, and pipelines. By the end of the book, you'll be able to build high-performing machine learning models using XGBoost with minimal errors and maximum speed. What you will learn Build gradient boosting models from scratch Develop XGBoost regressors and classifiers with accuracy and speed Analyze variance and bias in terms of fine-tuning XGBoost hyperparameters Automatically correct missing values and scale imbalanced data Apply alternative base learners like dart, linear models, and XGBoost random forests Customize transformers and pipelines to deploy XGBoost models Build non-correlated ensembles and stack XGBoost models to increase accuracy Who this book is for This book is for data science professionals and enthusiasts, data analysts, and developers who want to build fast and accurate machine learning models that scale with big data. Proficiency in Python, along with a basic understanding of linear algebra, will help you to get the most out of this book.
Applications Of Artificial Intelligence In Mining And Geotechnical Engineering
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Author : Hoang Nguyen
language : en
Publisher: Elsevier
Release Date : 2023-11-20
Applications Of Artificial Intelligence In Mining And Geotechnical Engineering written by Hoang Nguyen and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-20 with Science categories.
Applications of Artificial Intelligence in Mining, Geotechnical and Geoengineering provides recent advances in mining, geotechnical and geoengineering, as well as applications of artificial intelligence in these areas. It serves as the first book on applications of artificial intelligence in mining, geotechnical and geoengineering, providing an opportunity for researchers, scholars, engineers, practitioners and data scientists from all over the world to understand current developments and applications. Topics covered include slopes, open-pit mines, quarries, shafts, tunnels, caverns, underground mines, metro systems, dams and hydro-electric stations, geothermal energy, petroleum engineering, and radioactive waste disposal. In the geotechnical and geoengineering aspects, topics of specific interest include, but are not limited to, foundation, dam, tunneling, geohazard, geoenvironmental and petroleum engineering, rock mechanics, geotechnical engineering, soil mechanics and foundation engineering, civil engineering, hydraulic engineering, petroleum engineering, engineering geology, etc. Guides readers through the process of gathering, processing, and analyzing datasets specifically tailored for mining, geotechnical, and engineering challenges. Examines the evolution and practical implementation of artificial intelligence models in predicting, forecasting, and optimizing solutions for mining, geotechnical, and engineering problems. Offers cutting-edge methodologies to address the most demanding and complex issues encountered in the fields of mining, geotechnical studies, and engineering.
Handbook Of Research On Machine Learning
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Author : Monika Mangla
language : en
Publisher: CRC Press
Release Date : 2022-08-04
Handbook Of Research On Machine Learning written by Monika Mangla and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-04 with Computers categories.
This volume takes the reader on a technological voyage of machine learning advancements, highlighting the systematic changes in algorithms, challenges, and constraints. The technological advancements in the ML arena have transformed and revolutionized several fields, including transportation, agriculture, finance, weather monitoring, and others. This book brings together researchers, authors, industrialists, and academicians to cover a vast selection of topics in ML, starting with the rudiments of machine learning approaches and going on to specific applications in healthcare and industrial automation. The book begins with an overview of the ethics, security and privacy issues, future directions, and challenges in machine learning as well as a systematic review of deep learning techniques and provides an understanding of building generative adversarial networks. Chapters explore predictive data analytics for health issues. The book also adds a macro dimension by highlighting the industrial applications of machine learning, such as in the steel industry, for urban information retrieval, in garbage detection, in measuring air pollution, for stock market predictions, for underwater fish detection, as a fake news predictor, and more.
Mining Data For Financial Applications
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Author : Valerio Bitetta
language : en
Publisher: Springer Nature
Release Date : 2021-01-14
Mining Data For Financial Applications written by Valerio Bitetta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-14 with Computers categories.
This book constitutes revised selected papers from the 5th Workshop on Mining Data for Financial Applications, MIDAS 2020, held in conjunction with ECML PKDD 2020, in Ghent, Belgium, in September 2020.* The 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with challenges, potentialities, and applications of leveraging data-mining tasks regarding problems in the financial domain. *The workshop was held virtually due to the COVID-19 pandemic. “Information Extraction from the GDELT Database to Analyse EU Sovereign Bond Markets” and “Exploring the Predictive Power of News and Neural Machine Learning Models for Economic Forecasting” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Applications Of Machine Learning And Deep Learning For Privacy And Cybersecurity
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Author : Lobo, Victor
language : en
Publisher: IGI Global
Release Date : 2022-06-24
Applications Of Machine Learning And Deep Learning For Privacy And Cybersecurity written by Lobo, Victor and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-24 with Computers categories.
The growth of innovative cyber threats, many based on metamorphosing techniques, has led to security breaches and the exposure of critical information in sites that were thought to be impenetrable. The consequences of these hacking actions were, inevitably, privacy violation, data corruption, or information leaking. Machine learning and data mining techniques have significant applications in the domains of privacy protection and cybersecurity, including intrusion detection, authentication, and website defacement detection, that can help to combat these breaches. Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity provides machine and deep learning methods for analysis and characterization of events regarding privacy and anomaly detection as well as for establishing predictive models for cyber attacks or privacy violations. It provides case studies of the use of these techniques and discusses the expected future developments on privacy and cybersecurity applications. Covering topics such as behavior-based authentication, machine learning attacks, and privacy preservation, this book is a crucial resource for IT specialists, computer engineers, industry professionals, privacy specialists, security professionals, consultants, researchers, academicians, and students and educators of higher education.
2019 Ieee 4th Advanced Information Technology Electronic And Automation Control Conference Iaeac
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Author : IEEE Staff
language : en
Publisher:
Release Date : 2019-12-20
2019 Ieee 4th Advanced Information Technology Electronic And Automation Control Conference Iaeac written by IEEE Staff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-20 with categories.
The aim objective of IAEAC 2019 is to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results and development activities in Information Technology and Artificial Intelligence This conference provides opportunities for the delegates to exchange new ideas and application experiences face to face, to establish business or research relations and to find global partners for future collaboration
Customization 4 0
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Author : Stephan Hankammer
language : en
Publisher: Springer
Release Date : 2018-06-20
Customization 4 0 written by Stephan Hankammer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-20 with Business & Economics categories.
This proceedings volume presents the latest research from the worldwide mass customization & personalization (MCP) community bringing together new thoughts and results from various disciplines within the field. The chapters are based on papers from the MCPC 2017. The book showcases research and practice from authors that see MCP as an opportunity to extend or even revolutionize current business models. The current trends of Industrie 4.0, digital manufacturing, and the rise of smart products allow for a fresh perspective on MCP: Customization 4.0. The book places a new set of values in the centre of the debate: a world with finite resources, global population growth, and exacerbating climate change needs smart thinking to engage the most effective capabilities and resources. It discusses how Customization 4.0 fosters sustainable development and creates shared value for companies, customers, consumers, and the society as a whole. The chapters of this book are contributed by a wide range of specialists, offering cutting-edge research, as well as insightful advances in industrial practice in key areas. The MCPC 2017 has a strong focus on real life MCP applications, and this proceedings volume reflects this. MCP strategies aim to profit from the fact that people are different. Their objective is to turn customer heterogeneities into opportunities, hence addressing “long tail” business models. The objective of MCP is to provide goods and services that best serve individual customers’ needs with near mass production efficiency. This proceedings volume highlights the interdisciplinary work of thought leaders, technology developers, and researchers with corporate entrepreneurs putting these strategies into practice. Chapter 24 is open access under a CC BY 4.0 license via link.springer.com.
Advances In Parallel Computing Algorithms Tools And Paradigms
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Author : D.J. Hemanth
language : en
Publisher: IOS Press
Release Date : 2022-11-23
Advances In Parallel Computing Algorithms Tools And Paradigms written by D.J. Hemanth and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-23 with Computers categories.
Recent developments in parallel computing for various fields of application are providing improved solutions for handling data. These newer, innovative ideas offer the technical support necessary to enhance intellectual decisions, while also dealing more efficiently with the huge volumes of data currently involved. This book presents the proceedings of ICAPTA 2022, the International Conference on Advances in Parallel Computing Technologies and Applications, hosted as a virtual conference from Bangalore, India, on 27 and 28 January 2022. The aim of the conference was to provide a forum for the sharing of knowledge about various aspects of parallel computing in communications systems and networking, including cloud and virtualization solutions, management technologies and vertical application areas. The conference also provided a premier platform for scientists, researchers, practitioners and academicians to present and discuss their most recent innovations, trends and concerns, as well as the practical challenges encountered in this field. More than 300 submissions were received for the conference, from which the 91 full-length papers presented here were accepted after review by a panel of subject experts. Topics covered include parallel computing in communication, machine learning intelligence for parallel computing and parallel computing for software services in theoretical and practical aspects. Providing an overview of recent developments in the field, the book will be of interest to all those whose work involves the use of parallel computing technologies.
Handbook Of Research On Machine Learning
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Author : Monika Mangla
language : en
Publisher: Apple Academic Press
Release Date : 2022
Handbook Of Research On Machine Learning written by Monika Mangla and has been published by Apple Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Machine learning categories.
An exploration of machine learning advancements. It covers many aspects in machine learning, along with the applications in healthcare, in the steel industry, for urban information retrieval, in garbage detection, in measuring air pollution, for stock market predictions, for underwater fish detection, as a fake news predictor, and more.