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R Data Structures and Algorithms电子书

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作       者:Dr. PKS Prakash

出  版  社:Packt Publishing

出版时间:2016-11-01

字       数:163.4万

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Increase speed and performance of your applications with efficient data structures and algorithms About This Book See how to use data structures such as arrays, stacks, trees, lists, and graphs through real-world examples Find out about important and advanced data structures such as searching and sorting algorithms Understand important concepts such as big-o notation, dynamic programming, and functional data structured Who This Book Is For This book is for R developers who want to use data structures efficiently. Basic knowledge of R is expected. What You Will Learn Understand the rationality behind data structures and algorithms Understand computation evaluation of a program featuring asymptotic and empirical algorithm analysis Get to know the fundamentals of arrays and linked-based data structures Analyze types of sorting algorithms Search algorithms along with hashing Understand linear and tree-based indexing Be able to implement a graph including topological sort, shortest path problem, and Prim’s algorithm Understand dynamic programming (Knapsack) and randomized algorithms In Detail In this book, we cover not only classical data structures, but also functional data structures. We begin by answering the fundamental question: why data structuresWe 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. Style and approach This easy-to-read book with its fast-paced nature will improve the productivity of an R programmer and improve the performance of R applications. It is packed with real-world examples.
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R Data Structures and Algorithms

R Data Structures and Algorithms

Credits

About the Authors

Acknowledgments

About the Reviewer

www.PacktPub.com

Why subscribe?

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

1. Getting Started

Introduction to data structure

Abstract data type and data structure

Relationship between problem and algorithm

Basics of R

Installation of R

Basic data types in R

Operations in R

Control structures in R

If condition

If...else condition

Ifelse function

For() loop

Nested for( ) loop

While loop

Special statements in loops

Break statement

Next statement

Repeat loop

First class functions in R

Exercises

Summary

2. Algorithm Analysis

Getting started with data structure

Memory management in R

System runtime in R

Best, worst, and average cases

Computer versus algorithm

Algorithm asymptotic analysis

Upper bounds or Big O notation

Lower bounds or Big Omega notation (Ω)

Big θ notation

Simplifying rules

Classifying rules

Computation evaluation of a program

Component 1 - Assignment operator

Component 2 - Simple loop

Component 3 - Complex loop

Component 4 - Loops with conditional statements

Component 5 - Recursive statements

Analyzing problems

Space bounds

Exercises

Summary

3. Linked Lists

Data types in R

Vector and atomic vector

Element data types

Factor

Matrix

Array

Dataframes

List

Object-oriented programming using R

Linked list

Linear linked list

Doubly linked list

Circular linked list

Array-based list

Analysis of list operations

Exercises

Summary

4. Stacks and Queues

Stacks

Array-based stacks

Linked stacks

Comparison of array-based and linked stacks

Implementing recursion

Queues

Array-based queues

Linked queues

Comparison of array-based and linked queues

Dictionaries

Exercises

Summary

5. Sorting Algorithms

Sorting terminology and notation

Three Θ(n²) sorting algorithms

Insertion sort

Bubble sort

Selection sort

The cost of exchange sorting

Shell sort

Merge sort

Quick sort

Heap sort

Bin sort and radix sort

An empirical comparison of sorting algorithms

Lower bounds for sorting

Exercises

Summary

6. Exploring Search Options

Searching unsorted and sorted vectors

Self-organizing lists

Heuristic 1 - Count

Heuristic 2 - Move-to-front

Heuristic 3 - Transpose

Hashing

Hash functions

Open hashing

Closed hashing

Bucket hashing

Linear probing

Analysis of closed hashing

Deletion

Exercises

Summary

7. Indexing

Linear indexing

ISAM

Tree-based indexing

2-3 trees

B-trees

B+ trees

B-tree analysis

Exercises

Summary

8. Graphs

Terminology and representations

Graph implementations

Graph traversals

Depth-first search

Breadth-first search

Topological sort

Shortest path problems

Single-source shortest paths

Minimum-cost spanning tree

Prim's algorithm

Kruskal's algorithm

Exercises

Summary

9. Programming and Randomized Algorithms

Dynamic programming

The knapsack problem

All pairs shortest paths

Randomized algorithms

Randomized algorithms for finding large values

Skip lists

Probabilistic analysis of skip lists

Exercises

Summary

10. Functional Data Structures

Functional data structure

Lazy evaluation

Functional stacks

Functional queues

Fast fully-persistent queues

Slowly-persistent queues and deques

Summary

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