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% Most of the following are not required for the majority
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% Document Info
\author{jandrade77}
\pdfinfo{
  /Title (clase-4.pdf)
  /Creator (Cheatography)
  /Author (jandrade77)
  /Subject (Clase 4 Cheat Sheet)
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\noindent
\begin{multicols}{3}
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    {\parbox{\dimexpr\textwidth-2\fboxsep\relax}{\noindent
        \hspace*{-6pt}\includegraphics[width=5.8cm]{/web/www.cheatography.com/public/images/cheatography_logo.pdf}}
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\begin{tabulary}{11cm}{L}
    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{Clase 4 Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{jandrade77} via \textcolor{DarkBackground}{\uline{cheatography.com/154857/cs/33141/}}}
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\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{LL}
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  \mymulticolumn{2}{p{5.377cm}}{\bf\textcolor{white}{Cheatographer}}  \\
  \vspace{-2pt}jandrade77 \\
  \uline{cheatography.com/jandrade77} \\
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  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Not Yet Published.\\
   Updated 14th July, 2022.\\
   Page {\thepage} of \pageref{LastPage}.
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  Measure your website readability!\\
  www.readability-score.com
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\begin{multicols*}{3}

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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{Regresión Logística}}  \tn
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\mymulticolumn{1}{x{5.377cm}}{La regresión logística es una herramienta estadística y de minería de datos que predice la probabilidad de un resultado que sólo puede tener dos valores (es decir, una variable Dicotómica). La predicción se basa en el uso de uno o varios predictores (numéricos y categóricos). El análisis de regresión logística se enmarca en el conjunto de Modelos Lineales Generalizados (GLM por sus siglas en inglés) que usa como función de enlace la función Logit, la cual se define a continuación:% Row Count 11 (+ 11)
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\mymulticolumn{1}{p{5.377cm}}{\vspace{1px}\centerline{\includegraphics[width=5.1cm]{/web/www.cheatography.com/public/uploads/jandrade77_1657763809_Captura de Pantalla 2022-07-13 a la(s) 21.56.10.png}}} \tn 
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\mymulticolumn{1}{x{5.377cm}}{Por lo tanto, se deben mantener las siguientes consideraciones: \newline • La Variable Dependiente debe ser dicotómica (poseer valores 0 y 1). \newline • Las Variables Independientes pueden ser cuantitativas o cualitativas, sin embargo, estas últimas se deben transformar a \newline variables cuantitativas. \newline • La ecuación oscila entre 0 y 1.}  \tn 
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\mymulticolumn{1}{x{5.377cm}}{{\bf{Propiedades de la Función}} \newline  \newline Por otro lado, una regresión logística produce una curva logística, que se limita a valores entre 0 y 1. La regresión logística es similar a una regresión lineal, pero la curva se construye utilizando el logaritmo natural de las "probabilidades" de la variable de destino, en lugar de la probabilidad. Por otra parte, los predictores no tienen que tener una distribución normal o tienen la misma diferencia en cada grupo.}  \tn 
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\mymulticolumn{1}{x{5.377cm}}{{\bf{Propiedades de la Función}} \newline  \newline En la regresión logística simple la constante (Beta 0) mueve la curva de la izquierda a la derecha y la pendiente (Beta 1) define la pendiente de la curva.}  \tn 
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% That's all folks
\end{multicols*}

\end{document}