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:
Release Date : 2018-03-14
Xgboost The Extreme Gradient Boosting For Mining Applications written by Nonita Sharma and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-14 with 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 t
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.
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.
Advanced Data Mining And Applications
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Author : Quan Z. Sheng
language : en
Publisher: Springer Nature
Release Date : 2024-12-12
Advanced Data Mining And Applications written by Quan Z. Sheng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-12 with Computers categories.
This six-volume set, LNAI 15387-15392, constitutes the refereed proceedings of the 20th International Conference on Advanced Data Mining and Applications, ADMA 2024, held in Sydney, New South Wales, Australia, during December 3–5, 2024. The 159 full papers presented here were carefully reviewed and selected from 422 submissions. These papers have been organized under the following topical sections across the different volumes: - Part I : Applications; Data mining. Part II : Data mining foundations and algorithms; Federated learning; Knowledge graph. Part III : Graph mining; Spatial data mining. Part IV : Health informatics. Part V : Multi-modal; Natural language processing. Part VI : Recommendation systems; Security and privacy issues.
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.
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.
Clinical Application Of Artificial Intelligence In Emergency And Critical Care Medicine Volume I
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Author : Zhongheng Zhang
language : en
Publisher: Frontiers Media SA
Release Date : 2022-02-03
Clinical Application Of Artificial Intelligence In Emergency And Critical Care Medicine Volume I written by Zhongheng Zhang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-03 with Medical categories.
Applications Of Remote Sensing Data In Mapping Of Forest Growing Stock And Biomass
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Author : José Aranha
language : en
Publisher: MDPI
Release Date : 2021-09-01
Applications Of Remote Sensing Data In Mapping Of Forest Growing Stock And Biomass written by José Aranha and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-01 with Science categories.
This Special Issue (SI), entitled "Applications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass”, resulted from 13 peer-reviewed papers dedicated to Forestry and Biomass mapping, characterization and accounting. The papers' authors presented improvements in Remote Sensing processing techniques on satellite images, drone-acquired images and LiDAR images, both aerial and terrestrial. Regarding the images’ classification models, all authors presented supervised methods, such as Random Forest, complemented by GIS routines and biophysical variables measured on the field, which were properly georeferenced. The achieved results enable the statement that remote imagery could be successfully used as a data source for regression analysis and formulation and, in this way, used in forestry actions such as canopy structure analysis and mapping, or to estimate biomass. This collection of papers, presented in the form of a book, brings together 13 articles covering various forest issues and issues in forest biomass calculation, constituting an important work manual for those who use mixed GIS and RS techniques.
Big Data Analytics For Smart Healthcare Applications
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Author : Celestine Iwendi
language : en
Publisher: Frontiers Media SA
Release Date : 2023-04-17
Big Data Analytics For Smart Healthcare Applications written by Celestine Iwendi and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-17 with Medical categories.
Iot Security Paradigms And Applications
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Author : Sudhir Kumar Sharma
language : en
Publisher: CRC Press
Release Date : 2020-10-08
Iot Security Paradigms And Applications written by Sudhir Kumar Sharma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-08 with Computers categories.
Integration of IoT (Internet of Things) with big data and cloud computing has brought forward numerous advantages and challenges such as data analytics, integration, and storage. This book highlights these challenges and provides an integrating framework for these technologies, illustrating the role of blockchain in all possible facets of IoT security. Furthermore, it investigates the security and privacy issues associated with various IoT systems along with exploring various machine learning-based IoT security solutions. This book brings together state-of-the-art innovations, research activities (both in academia and in industry), and the corresponding standardization impacts of 5G as well. Aimed at graduate students, researchers in computer science and engineering, communication networking, IoT, machine learning and pattern recognition, this book Showcases the basics of both IoT and various security paradigms supporting IoT, including Blockchain Explores various machine learning-based IoT security solutions and highlights the importance of IoT for industries and smart cities Presents various competitive technologies of Blockchain, especially concerned with IoT security Provides insights into the taxonomy of challenges, issues, and research directions in IoT-based applications Includes examples and illustrations to effectively demonstrate the principles, algorithm, applications, and practices of security in the IoT environment