%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % LaTeX Template: Project Titlepage Modified (v 0.1) by rcx % % Original Source: http://www.howtotex.com % Date: February 2014 % % This is a title page template which be used for articles & reports. % % This is the modified version of the original Latex template from % aforementioned website. % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \documentclass[12pt]{llncs} %{article} \usepackage[a4paper]{geometry} \usepackage[myheadings]{fullpage} \usepackage{fancyhdr} \usepackage{lastpage} \usepackage{graphicx, wrapfig, subcaption, setspace, booktabs} \usepackage[T1]{fontenc} \usepackage[font=small, labelfont=bf]{caption} \usepackage{fourier} \usepackage[protrusion=true, expansion=true]{microtype} \usepackage[english]{babel} \usepackage{sectsty} \usepackage{url, lipsum} \usepackage[utf8]{inputenc} \usepackage{float} \restylefloat{table} \newcommand{\HRule}[1]{\rule{\linewidth}{#1}} \begin{document} \title{Letter dataset: Results of Text mining project 2020} \date{} \author{Your name and UCO} \institute{PA164 and KD Lab FI MU Brno} \maketitle \begin{abstract} This work addresses the problem of ... \end{abstract} \section{Data set and task description} \subsection{Data set} link to the data set, number of instances, features, missing values etc , data preparation (e.g. transformation into form) \subsection{Data set reduction} \subsubsection{Feature reduction} introduce the learning curve, explain what number of feature you will use and why \subsubsection{Other reduction} voluntary; only in the case that you need eg. limit the number of instances \section{Description of the method used} \subsection{General} what classifiers (CLF) and what outlier detection (OD) methods you used. Do not describe them. \subsection{Document-term matrix} what representation (pre-processing, PP) you used (very likely binary, TF, TF/IDF) \section{Results} \subsection{Overview} general description of your results \subsection{Comparison of different combinations of (PP+OD+CLF)} including graphs and statistical tests. Which combination was the best in term of accuracy. Is that combination PP+OD+CLF significantly better that the others? %https://is.muni.cz/auth/el/fi/podzim2020/PA164/projekt/Statistical_Comparison_of_Classifiers_over_Multiple_Data_Sets.pdf} \subsection{Discussion} including discussion of the outliers that you found interesting \section{Conclusion} \section{References} only if you employed something uncommon. \end{document}