Scientific Writing for Computer Science Students - FTP Directory ...

More documents

Recommendations

Info

6.11. SPECIAL LATEX NOTES 111\item[Step 3] If $y \leg n$ return Step 1.\end{itemize}outputsStep 1 x = x + 1Step 2 y = x 2 + 1Step 3 If y ≤ n return Step 1.6.11.3 FootnotesFootnotes 1 are achieved by command \footnote{text}.6.11.4 Font sizeFont size can be enlarged or shrunk by special commands\Huge \LARGE \Large \tiny\footnotesizeetc. See latex manual! E.g. if your table contains a lot of text, first try toprune the text, but if it doesn’t help, you can use footnote size:\begin{center}\begin{table}[!h]\caption{plaa-plaa}\label{tab1:3}\footnotesize{\begin{tabular}\end{tabular}}\end{table}\end{center}6.11.5 Multi-column tablesIf you want to get a table, where some columns are divided into subcolumnson some rows but united in others, you can use command \multicolumn.This command requires package multicol. Include it in the header by command\usepackage{multicol}.
112 CHAPTER 6. L A TEXINSTRUCTIONS AND EXERCISESTable 6.3: Comparison of prediction accuracy of LR and NB models. Theprediction accuracy is expressed true positive T P and true negative T Nrates. All models have been evaluated by 10-fold cross-validation and theclassification rates have been averaged.Model structure LR rates NB ratesTP TN TP TNA ⇒ F R1 0.83 0.47 0.96 0.31A, B ⇒ F R1 0.91 0.72 0.80 0.81A, B, C ⇒ F R1 0.93 0.81 0.83 0.81T P 1 ⇒ F R2 0.70 0.68 0.96 0.53T P 1, D ⇒ F R2 0.78 0.84 0.76 0.61T P 1, D, E ⇒ F R2 0.76 0.89 0.82 0.87T P 1, D, E, F ⇒ F R2 0.70 0.92 0.80 0.87See the following example:\begin{table}[!h]\begin{center}\caption{Comparison of prediction accuracy of {\em LR} and {\em NB} models.The prediction accuracy is expressedtrue positive $TP$ and true negative $TN$ rates.All models have been evaluated by 10-fold cross-validation and theclassification rates have been averaged.}\label{crossval}\begin{tabular}{|l|c|c|c|c|}\hlineModel structure&\multicolumn{2}{|l|}{$LR$ rates} &\multicolumn{2}{|l|}{$NB$ rates}\\& TP& TN& TP&TN\\\hline$A \Rightarrow FR1$ &0.83&0.47&0.96&0.31\\\hline$A,B \Rightarrow FR1$ &0.91&0.72&0.80&0.81\\\hline$A,B,C \Rightarrow FR1$ &0.93&0.81&0.83&0.81\\\hline$TP1 \Rightarrow FR2 $&0.70&0.68&0.96&0.53\\1 These not recommended in computer science texts; use them sparsely!
Page 1 and 2:
Scientific Writing for ComputerScie
Page 3 and 4:
Contents1 Introduction 11.1 Goal 1:
Page 5 and 6:
CONTENTS 54.5.5 Phrases . . . . . .
Page 7 and 8:
CONTENTS 76.9.1 Idea . . . . . . .
Page 9 and 10:
2 CHAPTER 1. INTRODUCTION1.1.1 Prob
Page 11 and 12:
4 CHAPTER 1. INTRODUCTIONAlg. 1 Wri
Page 13 and 14:
6 CHAPTER 1. INTRODUCTION5. Final w
Page 15 and 16:
8 CHAPTER 1. INTRODUCTION• Weed o
Page 17 and 18:
10 CHAPTER 1. INTRODUCTIONHints:•
Page 19:
12CHAPTER 2. SEARCHING, READING, AN
Page 22 and 23:
2.5. REFERENCES 15• Sometimes the
Page 24 and 25:
2.5. REFERENCES 17Examples:A journa
Page 26 and 27:
2.5. REFERENCES 19• If an article
Page 28 and 29:
2.7. YOUR OWN OPINIONS? 21• If yo
Page 30 and 31:
Chapter 3Use of tables, figures,exa
Page 32 and 33:
3.2. LISTS 25• The tables are enc
Page 34 and 35:
3.5. EXAMPLES AND DEFINITIONS 27•
Page 36 and 37:
3.6. EQUATIONS 293.6.3 Text inside
Page 38 and 39:
Chapter 4Grammar with style notesVe
Page 40 and 41:
4.1. VERBS 334.1.3 Active or passiv
Page 42 and 43:
4.1. VERBS 35• ”be verb+ing”
Page 44 and 45:
4.2. NOUNS 37ExerciseRead the given
Page 46 and 47:
4.2. NOUNS 39”Statistics is the p
Page 48 and 49:
4.4. ARTICLES 41• Some common phr
Page 50 and 51:
4.4. ARTICLES 43When you refer to t
Page 52 and 53:
4.4. ARTICLES 451. Without any arti
Page 54 and 55:
4.4. ARTICLES 47ExercisesTask 1: Ad
Page 56 and 57:
4.4. ARTICLES 49• weakness• use
Page 58 and 59:
4.5. PRONOUNS 514.5.4 Many vs. seve
Page 60 and 61:
4.6. ADJECTIVES 53Adjective type Co
Page 62 and 63:
4.7. ADVERBS 552. in the end, when
Page 64 and 65:
4.8. PARALLEL STRUCTURES 57• far,
Page 66 and 67:
4.8. PARALLEL STRUCTURES 59• Chan
Page 68 and 69: 4.8. PARALLEL STRUCTURES 61either -
Page 70 and 71: 4.9. PREPOSITIONS 634.9.1 Expressin
Page 72 and 73: 4.9. PREPOSITIONS 65opportunity of/
Page 74 and 75: 4.10. SENTENCES 672. Relative claus
Page 76 and 77: 4.10. SENTENCES 69• Adverbs which
Page 78 and 79: 4.10. SENTENCES 712. a conditional
Page 80 and 81: 4.10. SENTENCES 73• However, when
Page 82 and 83: 4.11. PARAGRAPHS 75• Other: For e
Page 84 and 85: 4.11. PARAGRAPHS 77If it is hard to
Page 86 and 87: 4.12. PUNCTUATION 79”Despite the
Page 88 and 89: 4.12. PUNCTUATION 814.12.6 Quotatio
Page 90 and 91: 4.14. ABBREVIATIONS 834.13.3 Posses
Page 92 and 93: Chapter 5Writing master’s thesis5
Page 94 and 95: 5.1. PARTS OF THE MASTER’S THESIS
Page 96 and 97: 5.2. MASTER’S THESIS PROCESS 895.
Page 98 and 99: 5.2. MASTER’S THESIS PROCESS 91
Page 100 and 101: Chapter 6LATEXinstructions and exer
Page 102 and 103: 6.3. BASIC LATEX 95• \begin{docum
Page 104 and 105: 6.4. WRITING EQUATIONS AND SPECIAL
Page 106 and 107: 6.5. WRITING REFERENCES 99Definitio
Page 108 and 109: 6.7. DRAWING FIGURES 101Figure 6.1:
Page 110 and 111: 6.8. SPELL CHECKING 103d+, −dq0 q
Page 112 and 113: 6.9. WRITING REFERENCES BY BIBTEX 1
Page 114 and 115: 6.10. WRITING ALGORITHMS IN LATEX 1
Page 116 and 117: 6.10. WRITING ALGORITHMS IN LATEX 1
Page 120 and 121: 6.11. SPECIAL LATEX NOTES 113\hline
Page 122 and 123: Chapter 7AppendicesAppendix A: A si
Page 124 and 125: 117\subsection{The title of the sec
Page 126 and 127: 119\title{The main title}\author{Yo
Page 128 and 129: 121\begin{figure}[!h]\begin{center}
Page 130: Bibliography[1] Barrass, R.: Scient
show all

Scientific Writing for Computer Science Students - FTP Directory ...

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?