This chapter focused on the fundamentals of programming and randomized algorithms. The chapter built on the programming concepts of dynamic programming, and presented the difference between dynamic programming and recursion. The DAGs was also introduced in this chapter, and how it can be used to set up dynamic programming was discussed. Two popular examples of the knapsack problem and two APSP were covered in this chapter, and their solutions using dynamic programming were presented. Randomized algorithms, Las Vegas and Monte Carlo, were introduced with their application in determining max value using randomization. This chapter also introduced skip lists and the extension to randomized skip lists. The probabilistic analysis of skip list was covered for major operations and data storage. The next chapter will introduce functional algorithms concepts. Functional algorithms provide the ability to write clean and clear code by eliminating state during runtime so that output is always...
R Data Structures and Algorithms
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R Data Structures and Algorithms
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Overview of this book
In this book, we cover not only classical data structures, but also functional data structures.
We begin by answering the fundamental question: why data structures? We then move on to cover the relationship
between data structures and algorithms, followed by an analysis and evaluation of algorithms. We introduce the fundamentals of data structures, such as lists, stacks, queues, and dictionaries, using real-world examples. We also cover topics such as indexing, sorting, and searching in depth.
Later on, you will be exposed to advanced topics such as graph data structures, dynamic programming, and randomized algorithms. You will come to appreciate the intricacies of high performance and scalable programming using R. We also cover special R data structures such as vectors, data frames, and atomic vectors.
With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. We will also explore the application of binary search and will go in depth into sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort.
Table of Contents (17 chapters)
R Data Structures and Algorithms
Credits
About the Authors
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
Free Chapter
Getting Started
Algorithm Analysis
Linked Lists
Stacks and Queues
Sorting Algorithms
Exploring Search Options
Graphs
Programming and Randomized Algorithms
Functional Data Structures
Customer Reviews