Tag Archives: Mining

Handbook of Statistical Analysis and Data Mining Applications

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Handbook of Statistical Analysis and Data Mining Applications

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Are you looking for a comprehensive guide to statistical analysis and data mining applications? Look no further than the Handbook of Statistical Analysis and Data Mining Applications!

This comprehensive handbook covers a wide range of topics, including predictive modeling, clustering, classification, and more. Whether you’re a beginner looking to learn the basics or an experienced analyst looking to expand your skills, this handbook has something for everyone.

With contributions from leading experts in the field, this handbook provides practical insights and real-world examples to help you apply statistical analysis and data mining techniques to your own projects. From healthcare to finance to marketing, this handbook covers a wide range of industries and applications.

So whether you’re a student, a researcher, or a professional looking to enhance your skills, the Handbook of Statistical Analysis and Data Mining Applications is the ultimate resource for all your data analysis needs. Get your copy today and take your data analysis skills to the next level!
#Handbook #Statistical #Analysis #Data #Mining #Applications

Data Mining: Concepts and Techniques by Han, Jiawei; Kamber, Micheline

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Data Mining: Concepts and Techniques by Han, Jiawei; Kamber, Micheline

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Data mining is a crucial aspect of modern business intelligence and decision-making processes. In the book “Data Mining: Concepts and Techniques” by Han, Jiawei; Kamber, Micheline, readers are introduced to the fundamental concepts and techniques of data mining.

The authors provide a comprehensive overview of data mining principles, methodologies, and tools, making it an essential resource for anyone looking to delve into the world of data analysis and extraction. From data preprocessing and data warehousing to clustering, classification, and anomaly detection, this book covers a wide range of topics that are vital for understanding and implementing effective data mining strategies.

Whether you are a beginner or an experienced professional, “Data Mining: Concepts and Techniques” offers valuable insights and practical guidance for leveraging data to drive business success. So, if you want to enhance your data mining skills and stay ahead in today’s data-driven world, this book is a must-read.
#Data #Mining #Concepts #Techniques #Han #Jiawei #Kamber #Micheline

Advances in Knowledge Discovery and Data Mining: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May … IV (Lecture Notes in Artificial Intelligence)

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Price: $64.99 - $8.69
(as of Dec 27,2024 18:35:34 UTC – Details)




Publisher ‏ : ‎ Springer; 1st ed. 2023 edition (May 31, 2023)
Language ‏ : ‎ English
Paperback ‏ : ‎ 372 pages
ISBN-10 ‏ : ‎ 3031333829
ISBN-13 ‏ : ‎ 978-3031333828
Item Weight ‏ : ‎ 1.15 pounds
Dimensions ‏ : ‎ 6.1 x 0.84 x 9.25 inches


Join us at the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2023) in Osaka, Japan this May for a groundbreaking event in the field of Knowledge Discovery and Data Mining.

This conference will feature the latest advances in artificial intelligence and machine learning, with a focus on cutting-edge research and innovative applications. With a diverse range of topics including data mining, machine learning, big data analytics, and more, PAKDD 2023 promises to be a must-attend event for researchers, practitioners, and industry experts alike.

Don’t miss this opportunity to collaborate with leading experts in the field, network with peers, and stay abreast of the latest trends and developments in knowledge discovery and data mining. Stay tuned for updates on keynote speakers, paper submissions, and more.

Mark your calendars for PAKDD 2023 in Osaka, Japan – we look forward to seeing you there!
#Advances #Knowledge #Discovery #Data #Mining #27th #PacificAsia #Conference #Knowledge #Discovery #Data #Mining #PAKDD #Osaka #Japan #Lecture #Notes #Artificial #Intelligence

Data Science for Business: What You Need to Know about Data Mining and Da – GOOD

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Data Science for Business: What You Need to Know about Data Mining and Da – GOOD

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ta Analysis

Data science has become a crucial tool for businesses looking to make informed decisions and drive growth. Two key components of data science are data mining and data analysis. Understanding these concepts is essential for any business looking to harness the power of data to drive success.

Data mining involves the process of discovering patterns and relationships within large sets of data. This can involve identifying trends, correlations, and anomalies that can provide valuable insights for businesses. By using advanced algorithms and techniques, data mining can help businesses uncover hidden patterns that can inform decision-making and drive strategic initiatives.

On the other hand, data analysis involves the process of examining, cleaning, and transforming data to extract meaningful insights. This can involve using statistical methods, machine learning algorithms, and visualization tools to analyze data and uncover valuable insights. Data analysis is essential for businesses looking to make sense of their data and use it to inform strategic decision-making.

In conclusion, data mining and data analysis are essential components of data science that can help businesses harness the power of data to drive success. By understanding these concepts and leveraging them effectively, businesses can make informed decisions, drive growth, and stay competitive in today’s data-driven world.
#Data #Science #Business #Data #Mining #GOOD

DATA MINING: NEXT GENERATION CHALLENGES AND FUTURE By Hillol Kargupta & Anupama

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DATA MINING: NEXT GENERATION CHALLENGES AND FUTURE By Hillol Kargupta & Anupama

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In this post, we will explore the next generation challenges and future of data mining as discussed by Hillol Kargupta and Anupama.

Data mining has come a long way since its inception, with advances in technology and the availability of massive amounts of data. However, with these advancements come new challenges that must be addressed in order to continue making strides in this field.

One of the key challenges facing data mining is the increasing complexity and size of data sets. As more and more data is being generated every day, traditional data mining techniques are struggling to keep up. This has led to the development of new algorithms and approaches that can handle the sheer volume of data being generated.

Another challenge is the issue of privacy and security. With the rise of data breaches and concerns over how personal data is being used, there is a growing need for data mining techniques that can protect sensitive information while still extracting valuable insights.

Additionally, as data becomes more interconnected and multidimensional, there is a need for data mining techniques that can handle complex relationships and patterns within the data. This requires a more holistic approach to data mining that looks beyond individual data points and considers the connections between them.

Looking to the future, Kargupta and Anupama discuss the potential for data mining to revolutionize industries such as healthcare, finance, and marketing. By leveraging the power of data mining, organizations can gain valuable insights that can drive innovation and improve decision-making.

Overall, the future of data mining is bright, but it will require continued innovation and collaboration to address the challenges that lie ahead. With the right tools and techniques, data mining has the potential to revolutionize how we use and analyze data in the years to come.
#DATA #MINING #GENERATION #CHALLENGES #FUTURE #Hillol #Kargupta #Anupama, artificial intelligence

Data Mining with R: Learning with Case Studies (Chapman & Hall/CRC Data M – GOOD

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Data Mining with R: Learning with Case Studies (Chapman & Hall/CRC Data M – GOOD

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Data Mining with R: Learning with Case Studies (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) – A Comprehensive Guide to R Programming for Data Mining

Are you interested in learning how to use R for data mining and analysis? Look no further than “Data Mining with R: Learning with Case Studies” by Chapman & Hall/CRC. This book is a comprehensive guide to using R programming language for data mining and knowledge discovery, with a focus on practical case studies.

The book covers a wide range of topics, including data exploration, data visualization, clustering, classification, association rules, and more. Each chapter includes detailed explanations, code examples, and case studies that demonstrate how to apply R to real-world data mining problems.

Whether you are new to R or an experienced user looking to expand your skills, “Data Mining with R: Learning with Case Studies” is a valuable resource for anyone interested in using R for data analysis. Get your copy today and start unlocking the power of R for data mining!
#Data #Mining #Learning #Case #Studies #Chapman #HallCRC #Data #GOOD

Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!)

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Price: $27.79
(as of Dec 27,2024 16:42:06 UTC – Details)




ASIN ‏ : ‎ B008S996FK
Publisher ‏ : ‎ Springer; 2011th edition (August 4, 2011)
Publication date ‏ : ‎ August 4, 2011
Language ‏ : ‎ English
File size ‏ : ‎ 6769 KB
Text-to-Speech ‏ : ‎ Not enabled
Enhanced typesetting ‏ : ‎ Not Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 374 pages

Customers say

Customers find the book helpful for learning data mining and predictive modeling. They find the writing style approachable and logical. The Rattle interface is described as easy and intuitive. The book provides practical examples and beautiful color plots.

AI-generated from the text of customer reviews


Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!)

Are you ready to unlock the hidden gems buried within your data? Look no further than Rattle and R, two powerful tools that will help you unearth insights and make sense of complex datasets.

Rattle is a graphical user interface for data mining using R, a programming language and software environment for statistical computing and graphics. With Rattle, you can easily explore, visualize, and model your data without needing to write code. It’s perfect for those new to data mining or looking for a user-friendly way to analyze their data.

R, on the other hand, is a versatile and powerful tool for data analysis, visualization, and machine learning. With a rich ecosystem of packages and libraries, R allows you to perform advanced statistical analyses and create stunning visualizations to communicate your findings effectively.

By combining Rattle and R, you can streamline your data mining process and uncover actionable insights that drive decision-making and inform strategy. Whether you’re a data scientist, analyst, or business professional, mastering these tools will give you a competitive edge in today’s data-driven world.

So don’t wait any longer – start exploring the art of excavating data for knowledge discovery with Rattle and R today!
#Data #Mining #Rattle #Art #Excavating #Data #Knowledge #Discovery

Machine Learning and Data Mining for Sports Analytics: 7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, … in Computer and Information Science)

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Price: $54.99 - $52.46
(as of Dec 27,2024 16:17:15 UTC – Details)




Publisher ‏ : ‎ Springer; 1st ed. 2020 edition (December 10, 2020)
Language ‏ : ‎ English
Paperback ‏ : ‎ 152 pages
ISBN-10 ‏ : ‎ 3030649113
ISBN-13 ‏ : ‎ 978-3030649111
Item Weight ‏ : ‎ 7.9 ounces
Dimensions ‏ : ‎ 6.1 x 0.35 x 9.25 inches


Machine Learning and Data Mining for Sports Analytics: 7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, Exploring the Latest Innovations in Sports Data Analysis

The intersection of machine learning, data mining, and sports analytics has revolutionized the way sports organizations and enthusiasts analyze and understand athletic performance. The 7th International Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA 2020) is set to take place in Ghent, Belgium, as part of the prestigious European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) 2020.

This workshop will bring together researchers, practitioners, and industry experts to discuss the latest advancements in using machine learning and data mining techniques to extract insights from sports data. From player performance analysis to injury prediction and game strategy optimization, MLSA 2020 will cover a wide range of topics that are shaping the future of sports analytics.

Attendees can expect to hear from leading experts in the field, participate in hands-on workshops, and network with like-minded professionals. Whether you are a data scientist, sports analyst, or sports enthusiast, MLSA 2020 offers a unique opportunity to learn about cutting-edge research and applications in sports analytics.

Don’t miss out on this exciting event in the beautiful city of Ghent, Belgium. Stay tuned for more updates on MLSA 2020 and join us in exploring the endless possibilities of machine learning and data mining in sports analytics.
#Machine #Learning #Data #Mining #Sports #Analytics #7th #International #Workshop #MLSA #Colocated #ECMLPKDD #Ghent #Belgium #Computer #Information #Science

Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia Conference, P

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Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia Conference, P

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acific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is one of the most prestigious conferences in the field of knowledge discovery and data mining. The 22nd edition of PAKDD was held recently, and it showcased some of the most cutting-edge research in the field.

One of the key highlights of the conference was the advances in machine learning algorithms and techniques. Researchers presented new models and methods for handling large-scale datasets, improving the accuracy and efficiency of data mining tasks. These advancements are crucial for various applications, such as predictive analytics, pattern recognition, and anomaly detection.

Another key theme of the conference was the integration of data mining with other disciplines, such as biology, healthcare, and finance. Researchers discussed how data mining techniques can be applied to solve real-world problems in these domains, leading to new insights and discoveries.

Overall, the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining showcased the latest advancements in the field and highlighted the importance of interdisciplinary collaboration in pushing the boundaries of knowledge discovery and data mining. Stay tuned for more updates and insights from the world of data mining!
#Advances #Knowledge #Discovery #Data #Mining #22nd #PacificAsia #Conference

Data Mining and Analysis: Fundamental Concepts and Algorithms

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Price: $51.99
(as of Dec 27,2024 14:40:32 UTC – Details)




ASIN ‏ : ‎ B08JZBT7VF
Publication date ‏ : ‎ September 23, 2020
Language ‏ : ‎ English
File size ‏ : ‎ 129022 KB
Simultaneous device usage ‏ : ‎ Unlimited
Text-to-Speech ‏ : ‎ Enabled
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 1645 pages

Customers say

Customers find the book comprehensive and helpful for learning about data mining. They appreciate the clear writing style and organization of the material. However, some readers feel the math content is too extensive with countless equations printed in small print.

AI-generated from the text of customer reviews


Data Mining and Analysis: Fundamental Concepts and Algorithms

In today’s data-driven world, the ability to extract valuable insights from vast amounts of data is crucial for making informed decisions. Data mining and analysis are essential techniques that enable organizations to uncover patterns, trends, and relationships within their data.

Data mining involves the process of discovering meaningful patterns and information from large datasets. This can include techniques such as clustering, classification, regression, and association rule mining. By applying data mining algorithms, businesses can gain valuable insights that can help improve decision-making, optimize processes, and identify opportunities for growth.

One of the fundamental concepts in data mining is the use of algorithms to extract valuable information from raw data. These algorithms are designed to perform specific tasks, such as pattern recognition, anomaly detection, and prediction. Some popular data mining algorithms include decision trees, k-means clustering, neural networks, and association rule mining.

It is important for organizations to understand the fundamental concepts and algorithms of data mining in order to effectively analyze and extract insights from their data. By leveraging these techniques, businesses can gain a competitive advantage, improve efficiency, and drive innovation.

In conclusion, data mining and analysis are powerful tools that can help organizations unlock the full potential of their data. By understanding the fundamental concepts and algorithms of data mining, businesses can harness the power of their data to make better decisions and drive success.
#Data #Mining #Analysis #Fundamental #Concepts #Algorithms