Random Forests
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Random Forests With R
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Author : Robin Genuer
language : en
Publisher: Springer Nature
Release Date : 2020-09-10
Random Forests With R written by Robin Genuer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-10 with Mathematics categories.
This book offers an application-oriented guide to random forests: a statistical learning method extensively used in many fields of application, thanks to its excellent predictive performance, but also to its flexibility, which places few restrictions on the nature of the data used. Indeed, random forests can be adapted to both supervised classification problems and regression problems. In addition, they allow us to consider qualitative and quantitative explanatory variables together, without pre-processing. Moreover, they can be used to process standard data for which the number of observations is higher than the number of variables, while also performing very well in the high dimensional case, where the number of variables is quite large in comparison to the number of observations. Consequently, they are now among the preferred methods in the toolbox of statisticians and data scientists. The book is primarily intended for students in academic fields such as statistical education, but also for practitioners in statistics and machine learning. A scientific undergraduate degree is quite sufficient to take full advantage of the concepts, methods, and tools discussed. In terms of computer science skills, little background knowledge is required, though an introduction to the R language is recommended. Random forests are part of the family of tree-based methods; accordingly, after an introductory chapter, Chapter 2 presents CART trees. The next three chapters are devoted to random forests. They focus on their presentation (Chapter 3), on the variable importance tool (Chapter 4), and on the variable selection problem (Chapter 5), respectively. After discussing the concepts and methods, we illustrate their implementation on a running example. Then, various complements are provided before examining additional examples. Throughout the book, each result is given together with the code (in R) that can be used to reproduce it. Thus, the book offers readers essential information and concepts, together with examples and the software tools needed to analyse data using random forests.
Topics In Random Forests
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Author : Chao Chen
language : en
Publisher:
Release Date : 2005
Topics In Random Forests written by Chao Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
Ai Meets Bi
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Author : Lakshman Bulusu
language : en
Publisher: CRC Press
Release Date : 2020-11-03
Ai Meets Bi written by Lakshman Bulusu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-03 with Computers categories.
With the emergence of Artificial Intelligence (AI) in the business world, a new era of Business Intelligence (BI) has been ushered in to create real-world business solutions using analytics. BI developers and practitioners now have tools and technologies to create systems and solutions to guide effective decision making. Decisions can be made on the basis of more reliable and accurate information and intelligence, which can lead to valuable, actionable insights for business. Previously, BI professionals were stymied by bad or incomplete data, poorly architected solutions, or even just outright incapable systems or resources. With the advent of AI, BI has new possibilities for effectiveness. This is a long-awaited phase for practitioners and developers and, moreover, for executives and leaders relying on knowledgeable and intelligent decision making for their organizations. Beginning with an outline of the traditional methods for implementing BI in the enterprise and how BI has evolved into using self-service analytics, data discovery, and most recently AI, AI Meets BI first lays out the three typical architectures of the first, second, and third generations of BI. It then takes an in-depth look at various types of analytics and highlights how each of these can be implemented using AI-enabled algorithms and deep learning models. The crux of the book is four industry use cases. They describe how an enterprise can access, assess, and perform analytics on data by way of discovering data, defining key metrics that enable the same, defining governance rules, and activating metadata for AI/ML recommendations. Explaining the implementation specifics of each of these four use cases by way of using various AI-enabled machine learning and deep learning algorithms, this book provides complete code for each of the implementations, along with the output of the code, supplemented by visuals that aid in BI-enabled decision making. Concluding with a brief discussion of the cognitive computing aspects of AI, the book looks at future trends, including augmented analytics, automated and autonomous BI, and security and governance of AI-powered BI.
Random Forests And Gene Selection To Classify Arabidopsis Thaliana Ecotypes
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Author : Hsueh-han Yeh
language : en
Publisher:
Release Date : 2007
Random Forests And Gene Selection To Classify Arabidopsis Thaliana Ecotypes written by Hsueh-han Yeh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Arabidopsis thaliana categories.
Toward Artificial General Intelligence
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Author : Victor Hugo C. de Albuquerque
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2023-11-06
Toward Artificial General Intelligence written by Victor Hugo C. de Albuquerque and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-06 with Computers categories.
Artificial Intelligence (AI) has been an exciting field of study and research in educational institutions and research labs across the globe. Technology giants and IT organizations invest heavily on AI technologies and tools with the aim of preciselyautomating a variety of simple as well as complicated business operations acrossindustry verticals. This book covers the latest trends and transitions happening in thefuturistic AI domain. The book also focuses on machine and deep learning (ML/DL)algorithms, which are, undoubtedly, the mainstream implementation technologies ofstate-of-the-art AI systems and services. Also, there are chapters on computer vision(CV) and natural language processing (NLP), the primary use cases and applicationsof AI. The book has well-written chapters for demystifying AI model engineeringmethods. Further on, our esteemed readers can fi nd details on AI model evaluation,optimization, deployment and observability. Finally, the book deals and describesgenerative AI, the latest buzzword in the IT industry. The book presents the recent ground-breaking changes taking place in the aspects of AI model building, hosting, running and maintaining in cloud environments, articulates and accentuates the most recent developments taking place in the domain of Artifi cial Intelligence, covers the noteworthy innovations and disruptions towards Generative Artificial Intelligence (Generative AI), explains the breakthrough innovations and disruptions towards Artifi cial General Intelligence (AGI) and delineates an engaging discussion of Natural Language Processing, Neuromorphic Systems and Biometrics.
Intelligent Systems Design And Applications
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Author : Ajith Abraham
language : en
Publisher: Springer
Release Date : 2019-04-13
Intelligent Systems Design And Applications written by Ajith Abraham and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-13 with Computers categories.
This book highlights recent research on Intelligent Systems and Nature Inspired Computing. It presents 212 selected papers from the 18th International Conference on Intelligent Systems Design and Applications (ISDA 2018) and the 10th World Congress on Nature and Biologically Inspired Computing (NaBIC), which was held at VIT University, India. ISDA-NaBIC 2018 was a premier conference in the field of Computational Intelligence and brought together researchers, engineers and practitioners whose work involved intelligent systems and their applications in industry and the “real world.” Including contributions by authors from over 40 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
Artificial Intelligence In Business
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Author : Pavankumar Gurazada & Seema Gupta
language : en
Publisher: Vikas Publishing House
Release Date :
Artificial Intelligence In Business written by Pavankumar Gurazada & Seema Gupta and has been published by Vikas Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Artificial Intelligence in Business is transforming the way organizations operate—driving innovation, increasing efficiency, and enabling smarter, data-driven decision making. Yet for many professionals and students, the gap between complex technical concepts and practical business applications can feel overwhelming. This book bridges that gap with clarity, relevance, and purpose. Designed for MBA students, business leaders, and aspiring AI practitioners, Artificial Intelligence in Business cuts through the hype to provide a grounded, accessible, and actionable guide to real world AI. From foundational principles like machine learning and deep learning to advanced applications in marketing, finance, supply chain, and HR, each chapter offers practical insights supported by real-world use cases and code implementations. Whether you're aiming to enhance customer engagement, streamline operations, or manage risk more effectively, this book equips you with the knowledge and tools to apply AI strategically in a business context.
Advances In Knowledge Discovery And Data Mining
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Author : Kamal Karlapalem
language : en
Publisher: Springer Nature
Release Date : 2021-05-07
Advances In Knowledge Discovery And Data Mining written by Kamal Karlapalem and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-07 with Computers categories.
The 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021. The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part III: Representation learning and embedding, and learning from data.
Fintech And The Emerging Ecosystems
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Author : Alex Zarifis
language : en
Publisher: Springer Nature
Release Date : 2025-07-02
Fintech And The Emerging Ecosystems written by Alex Zarifis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-02 with Business & Economics categories.
Financial technologies, commonly referred to as Fintech, are revolutionizing and reorganizing the financial sector. This digital transformation profoundly impacts society and influences our everyday lives in numerous ways, as financial services intersect with various other services we utilize. This book offers contributions from leading researchers in the field, providing a comprehensive understanding of this multifaceted transformation. It encompasses emerging financial technologies such as cryptoassets, including Bitcoin and Non-Fungible Tokens (NFTs), Decentralized Finance (DeFi), Central Bank Digital Currencies (CBDCs), and the growing significance of Artificial Intelligence (AI) and Generative AI. While the primary audience comprises researchers and academics, practitioners and students can also glean practical insights from its contents. Chapters "A Model of Trust in Central Bank Digital Currency (CBDC) in Brazil: How Trust in a Two-Tier CBDC with Both the Central and Retail Banks Involved Changes Consumer Trust" and "Building Trust in AI: Leadership Insights from Malaysian Fintech Boards" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Machine Learning With Lightgbm And Python
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Author : Andrich van Wyk
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-09-29
Machine Learning With Lightgbm And Python written by Andrich van Wyk 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 2023-09-29 with Computers categories.
Take your software to the next level and solve real-world data science problems by building production-ready machine learning solutions using LightGBM and Python Key Features Get started with LightGBM, a powerful gradient-boosting library for building ML solutions Apply data science processes to real-world problems through case studies Elevate your software by building machine learning solutions on scalable platforms Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMachine Learning with LightGBM and Python is a comprehensive guide to learning the basics of machine learning and progressing to building scalable machine learning systems that are ready for release. This book will get you acquainted with the high-performance gradient-boosting LightGBM framework and show you how it can be used to solve various machine-learning problems to produce highly accurate, robust, and predictive solutions. Starting with simple machine learning models in scikit-learn, you’ll explore the intricacies of gradient boosting machines and LightGBM. You’ll be guided through various case studies to better understand the data science processes and learn how to practically apply your skills to real-world problems. As you progress, you’ll elevate your software engineering skills by learning how to build and integrate scalable machine-learning pipelines to process data, train models, and deploy them to serve secure APIs using Python tools such as FastAPI. By the end of this book, you’ll be well equipped to use various -of-the-art tools that will help you build production-ready systems, including FLAML for AutoML, PostgresML for operating ML pipelines using Postgres, high-performance distributed training and serving via Dask, and creating and running models in the Cloud with AWS Sagemaker.What you will learn Get an overview of ML and working with data and models in Python using scikit-learn Explore decision trees, ensemble learning, gradient boosting, DART, and GOSS Master LightGBM and apply it to classification and regression problems Tune and train your models using AutoML with FLAML and Optuna Build ML pipelines in Python to train and deploy models with secure and performant APIs Scale your solutions to production readiness with AWS Sagemaker, PostgresML, and Dask Who this book is forThis book is for software engineers aspiring to be better machine learning engineers and data scientists unfamiliar with LightGBM, looking to gain in-depth knowledge of its libraries. Basic to intermediate Python programming knowledge is required to get started with the book. The book is also an excellent source for ML veterans, with a strong focus on ML engineering with up-to-date and thorough coverage of platforms such as AWS Sagemaker, PostgresML, and Dask.