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1. |
Record Nr. |
UNINA9910438147203321 |
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Autore |
Ohri A |
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Titolo |
R for business analytics / / A. Ohri |
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Pubbl/distr/stampa |
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New York, : Springer, 2012 |
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ISBN |
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1-283-62397-8 |
9786613936424 |
1-4614-4343-1 |
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Edizione |
[1st ed. 2013.] |
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Descrizione fisica |
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1 online resource (319 p.) |
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Disciplina |
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658.4/0302855133 |
658.4720285555 |
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Soggetti |
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R (Computer program language) |
Business enterprises |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Why R -- R Infrastructure -- R Interfaces -- Manipulating Data -- Exploring Data -- Building Regression Models -- Data Mining using R -- Clustering and Data Segmentation -- Forecasting and Time-Series Models -- Data Export and Output -- Optimizing your R Coding -- Additional Training Literature -- Appendix. |
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Sommario/riassunto |
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R for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages. With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness. The use of Graphical User Interfaces (GUI) is emphasized in this book to further cut down and bend the famous learning curve in learning R. This book is aimed to help you kick-start with analytics including chapters on data visualization, code examples on web analytics and social media analytics, clustering, regression models, text mining, data mining models and forecasting. The book tries to expose the reader to a breadth of business analytics topics without burying the user in needless depth. The included references and links allow the reader to pursue business analytics topics. This book is aimed at business analysts with basic programming skills for using R for Business |
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Analytics. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. Business analytics (BA) refers to the field of exploration and investigation of data generated by businesses. Business Intelligence (BI) is the seamless dissemination of information through the organization, which primarily involves business metrics both past and current for the use of decision support in businesses. Data Mining (DM) is the process of discovering new patterns from large data using algorithms and statistical methods. To differentiate between the three, BI is mostly current reports, BA is models to predict and strategize and DM matches patterns in big data. The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy. . |
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2. |
Record Nr. |
UNINA9910847590503321 |
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Autore |
Barolli Leonard |
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Titolo |
Advanced Information Networking and Applications : Proceedings of the 38th International Conference on Advanced Information Networking and Applications (AINA-2024), Volume 3 / / edited by Leonard Barolli |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (486 pages) |
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Collana |
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Lecture Notes on Data Engineering and Communications Technologies, , 2367-4520 ; ; 201 |
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Disciplina |
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Soggetti |
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Engineering - Data processing |
Computational intelligence |
Artificial intelligence |
Data Engineering |
Computational Intelligence |
Artificial Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Efficient Communication Protocol for Programmable Matter -- IoRT-based Distributed Algorithm for Robust Team Formation and its Application to Smart City Operation -- A WSN and Vision based Energy Efficient and Smart Surveillance System using Computer Vision and AI at Edge -- Mitigating Resource Depletion and Message Sequencing Attacks in SCADA Systems -- API Descriptions for the Web of Things -- SmartDriveAuth: Enhancing Vehicle Security with Continuous Driver Authentication via Wearable PPG Sensors and Deep Learning -- A Vision Transformer Based Indoor Localization Using CSI Signals in IoT Networks -- Deep Reinforcement Learning for VNF Placement and Chaining of Cloud Network Services -- Optimising Water Quality Classification in Aquaculture Using a New Parameter Pre-selection Approach -- Topic Analysis of Japanese Sentences Using Sentence Embeddings -- Performance Improvement of Semantic Search Using Sentence Embeddings by Dimensionality Reduction -- A Fuzzy-based System for Assessment of Performance Error in VANETs -- Carbon Credits Price Prediction Model (CCPPM) -- Experimental Exploration of the Power of Conditional GAN in Image Reconstruction-based Adversarial Attack Defense Strategies -- Framework for Cognitive Self-Healing of Real Broadband Networks -- Honey Bee Inspired Routing Algorithm for Sparse Unstructured P2P Networks. |
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Sommario/riassunto |
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Networks of today are going through a rapid evolution and there are many emerging areas of information networking and their applications. Heterogeneous networking supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities such as sensing, communications, intelligence, and actuations are emerging as a critically important disruptive computer class based on a new platform, networking structure and interface that enable novel, low-cost and high-volume applications. Several of such applications have been difficult to realize because of many interconnection problems. To fulfill their large range of applications different kinds of networks need to collaborate and wired and next generation wireless systems should be integrated in order to develop high performance computing solutions to problems arising from the complexities of these networks. This book covers the theory, design and applications of computer networks, distributed computing, and information systems. The aim of the book “Advanced Information Networking and Applications” is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and applications. |
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