\documentclass[10pt,a4paper]{article}

% Packages
\usepackage{fancyhdr}           % For header and footer
\usepackage{multicol}           % Allows multicols in tables
\usepackage{tabularx}           % Intelligent column widths
\usepackage{tabulary}           % Used in header and footer
\usepackage{hhline}             % Border under tables
\usepackage{graphicx}           % For images
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%\usepackage[utf8x]{inputenc}    % For unicode character support
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\usepackage{colortbl}           % For coloured tables
\usepackage{setspace}           % For line height
\usepackage{lastpage}           % Needed for total page number
\usepackage{seqsplit}           % Splits long words.
%\usepackage{opensans}          % Can't make this work so far. Shame. Would be lovely.
\usepackage[normalem]{ulem}     % For underlining links
% Most of the following are not required for the majority
% of cheat sheets but are needed for some symbol support.
\usepackage{amsmath}            % Symbols
\usepackage{MnSymbol}           % Symbols
\usepackage{wasysym}            % Symbols
%\usepackage[english,german,french,spanish,italian]{babel}              % Languages

% Document Info
\author{lkakashv}
\pdfinfo{
  /Title (scikit-learn.pdf)
  /Creator (Cheatography)
  /Author (lkakashv)
  /Subject (Scikit-learn Cheat Sheet)
}

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% This two commands together give roughly
% the right line height in the tables
\renewcommand{\arraystretch}{1.3}
\onehalfspacing

% Commands
\newcommand{\SetRowColor}[1]{\noalign{\gdef\RowColorName{#1}}\rowcolor{\RowColorName}} % Shortcut for row colour
\newcommand{\mymulticolumn}[3]{\multicolumn{#1}{>{\columncolor{\RowColorName}}#2}{#3}} % For coloured multi-cols
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% Font and Colours
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\renewcommand{\familydefault}{\sfdefault}
\color{TextColor}

% Header and Footer
\pagestyle{fancy}
\fancyhead{} % Set header to blank
\fancyfoot{} % Set footer to blank
\fancyhead[L]{
\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{C}
    \SetRowColor{DarkBackground}
    \vspace{-7pt}
    {\parbox{\dimexpr\textwidth-2\fboxsep\relax}{\noindent
        \hspace*{-6pt}\includegraphics[width=5.8cm]{/web/www.cheatography.com/public/images/cheatography_logo.pdf}}
    }
\end{tabulary}
\columnbreak
\begin{tabulary}{11cm}{L}
    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{Scikit-learn Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{lkakashv} via \textcolor{DarkBackground}{\uline{cheatography.com/172895/cs/36333/}}}
\end{tabulary}
\end{multicols}}

\fancyfoot[L]{ \footnotesize
\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{LL}
  \SetRowColor{FootBackground}
  \mymulticolumn{2}{p{5.377cm}}{\bf\textcolor{white}{Cheatographer}}  \\
  \vspace{-2pt}lkakashv \\
  \uline{cheatography.com/lkakashv} \\
  \end{tabulary}
\vfill
\columnbreak
\begin{tabulary}{5.8cm}{L}
  \SetRowColor{FootBackground}
  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Published 23rd October, 2023.\\
   Updated 2nd January, 2023.\\
   Page {\thepage} of \pageref{LastPage}.
\end{tabulary}
\vfill
\columnbreak
\begin{tabulary}{5.8cm}{L}
  \SetRowColor{FootBackground}
  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Sponsor}}  \\
  \SetRowColor{white}
  \vspace{-5pt}
  %\includegraphics[width=48px,height=48px]{dave.jpeg}
  Measure your website readability!\\
  www.readability-score.com
\end{tabulary}
\end{multicols}}




\begin{document}
\raggedright
\raggedcolumns

% Set font size to small. Switch to any value
% from this page to resize cheat sheet text:
% www.emerson.emory.edu/services/latex/latex_169.html
\footnotesize % Small font.

\begin{multicols*}{2}

\begin{tabularx}{8.4cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{8.4cm}}{\bf\textcolor{white}{Linear Regression}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{8.4cm}}{\# Import and create the model: \newline  \newline from sklearn.linear\_model import LinearRegression \newline   \newline your\_model = LinearRegression() \newline  \newline \# Fit: \newline  \newline your\_model.fit(x\_training\_data, y\_training\_data) \newline \# .coef\_: contains the coefficients \newline \# .intercept\_: contains the intercept \newline  \newline \# Predict: \newline  \newline predictions = \seqsplit{your\_model.predict(your\_x\_data)} \newline \#.score(): returns the coefficient of determination R$^{\textrm{2}}$} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{8.4cm}}{\bf\textcolor{white}{Naive Bayes}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{8.4cm}}{\# Import and create the model: \newline  \newline from sklearn.naive\_bayes import MultinomialNB \newline   \newline your\_model = MultinomialNB() \newline  \newline \# Fit: \newline  \newline your\_model.fit(x\_training\_data, y\_training\_data) \newline  \newline \# Predict: \newline  \newline \# Returns a list of predicted classes - one prediction for every data point \newline predictions = \seqsplit{your\_model.predict(your\_x\_data)} \newline   \newline \# For every data point, returns a list of probabilities of each class \newline probabilities = \seqsplit{your\_model.predict\_proba(your\_x\_data)}} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{8.4cm}}{\bf\textcolor{white}{K-Nearest Neighbors}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{8.4cm}}{\# Import and create the model: \newline  \newline from sklearn.neigbors import KNeighborsClassifier \newline   \newline your\_model = KNeighborsClassifier() \newline  \newline \# Fit: \newline  \newline your\_model.fit(x\_training\_data, y\_training\_data) \newline  \newline \# Predict: \newline  \newline \# Returns a list of predicted classes - one prediction for every data point \newline predictions = \seqsplit{your\_model.predict(your\_x\_data)} \newline   \newline \# For every data point, returns a list of probabilities of each class \newline probabilities = \seqsplit{your\_model.predict\_proba(your\_x\_data)}} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{8.4cm}}{\bf\textcolor{white}{K-Means}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{8.4cm}}{\# Import and create the model: \newline  \newline from sklearn.cluster import KMeans \newline   \newline your\_model = KMeans(n\_clusters=4, init='random') \newline n\_clusters: number of clusters to form and number of centroids to generate \newline init: method for initialization \newline k-means++: K-Means++ {[}default{]} \newline random: K-Means \newline random\_state: the seed used by the random number generator {[}optional{]} \newline  \newline \# Fit: \newline  \newline your\_model.fit(x\_training\_data) \newline  \newline \# Predict: \newline  \newline predictions = \seqsplit{your\_model.predict(your\_x\_data)}} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{8.4cm}}{\bf\textcolor{white}{Validating the Model}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{8.4cm}}{\# Import and print accuracy, recall, precision, and F1 score: \newline  \newline from sklearn.metrics import accuracy\_score, recall\_score, precision\_score, f1\_score \newline   \newline print(accuracy\_score(true\_labels, guesses)) \newline print(recall\_score(true\_labels, guesses)) \newline print(precision\_score(true\_labels, guesses)) \newline print(f1\_score(true\_labels, guesses)) \newline  \newline \# Import and print the confusion matrix: \newline  \newline from sklearn.metrics import confusion\_matrix \newline   \newline print(confusion\_matrix(true\_labels, guesses))} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{8.4cm}}{\bf\textcolor{white}{Training Sets and Test Sets}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{8.4cm}}{from sklearn.model\_selection import train\_test\_split \newline   \newline x\_train, x\_test, y\_train, y\_test = train\_test\_split(x, y, train\_size=0.8, test\_size=0.2) \newline  \newline \# train\_size: the proportion of the dataset to include in the train split \newline \# test\_size: the proportion of the dataset to include in the test split \newline \# random\_state: the seed used by the random number generator {[}optional{]}} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}


% That's all folks
\end{multicols*}

\end{document}