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  /Creator (Cheatography)
  /Author (esepulveda)
  /Subject (G8: Modelamiento predictivo para Ciencias de datos Cheat Sheet)
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    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{G8: Modelamiento predictivo para Ciencias de datos Cheat Sheet}}}} \\
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   \vspace{-2pt}Not Yet Published.\\
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{1.1 ANÁLISIS PREDICTIVO}}  \tn
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\mymulticolumn{1}{x{5.377cm}}{El análisis predictivo consiste en la tecnología que aprende de la experiencia para predecir el futuro comportamiento de individuos para tomar mejores decisiones.  `INFORMS Institute for Operations Research and the Management Sciences`}  \tn 
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\begin{tabularx}{5.377cm}{X}
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{1.4 PROCESO KDD}}  \tn
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\mymulticolumn{1}{x{5.377cm}}{Proceso de Extracción del Conocimiento conocido como Knowledge Discovery in Databases KDD}  \tn 
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{1.5 KDD - Selección de los Datos}}  \tn
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\mymulticolumn{1}{x{5.377cm}}{{\bf{Exploración de los datos :}}  Base Original -\textgreater{} Tablón de Datos (Minable) \newline  \newline {\bf{Muestra de entrenamiento :}}  Un subconjunto para entrenar un Modelo \newline {\bf{Muestra de validación :}} Un subconjunto para probar el modelo entrenado}  \tn 
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{2.2 CONCEPTOS ESTADISTICA DESCRIPTIVA}}  \tn
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\mymulticolumn{1}{x{5.377cm}}{{\bf{La población}}, es el conjunto total de objetos o personas de interés en un estudio. {\emph{una característica relevante es todos sus elementos deben cumplir con un conjunto predefinido de características}}. \newline {\bf{La Muestra}} es el subconjunto de la población, la cual se utiliza para estudiar las características de la población en general. Estas deben ser: Aleatorias y representativas. \newline {\bf{Variable Aleatoria}} cualquier característica que tome dos o más valores en una población.}  \tn 
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{3 PREDICIÓN LINEAL}}  \tn
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\mymulticolumn{1}{x{5.377cm}}{{\bf{MCO}} Minimo cuadrado Ordinario}  \tn 
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\mymulticolumn{1}{x{5.377cm}}{{\bf{¿Qué es el Bias?}} \newline El bias o sesgo puede ser pensado como un modelo que no ha tenido en cuenta toda la información disponible en el set de datos, lo que dificulta predicciones precisas. \newline  \newline {\bf{¿Qué es la varianza?}} \newline La Varianza es una medida de dispersión que se utiliza para representar la variabilidad de un conjunto de datos respecto de la media aritmética de los mismo.}  \tn 
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1. Análisis Descriptivo Univariado & Evaluar mediad de tendencia central ( Mediana, Moda), de dispersión. Los datos null se replazan por 0 \tn 
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3. Análisis Descriptivo Temporal (de Proporciones) & Debe contar con estabilidad temporal de proporciones. \tn 
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4. Análisis Descriptivo Temporal (de Predicción) & Busqca predecir el comportamiento de una variable en particular. \tn 
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{MODELOS KDD - SEMMA - CRISP}}  \tn
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{2.3 TIPOS DE VARIABLES ALEATORIAS}}  \tn
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\mymulticolumn{1}{x{5.377cm}}{{\bf{Variable Cualitativa}} \newline {\emph{Ordinal}} presenta modalidades no numéricas, en las que existe un orden por Ej: notas en un examen. \newline {\emph{Nominal}} presenta modalidades no numéricas que no admiten un criterio de orden. Ej: El estado civil, con las siguientes modalidades: sol, cas, sep, divor y viudo. \newline {\bf{Variable Cuantitativa}} \newline {\emph{Discreta}} puede asumir un número contable de valores: Ej: \# hijos en una familita. \newline {\emph{Continua}} puede asumir un número incontable de valores. Ej: peso de una persona.}  \tn 
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{4 REGRESIÓN LOGISTICA}}  \tn
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{1.3 SOBREAJUSTE E INFRAJUSTE}}  \tn
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\mymulticolumn{1}{x{5.377cm}}{{\bf{Overfitting}} \newline Se produce cuando un modelo modela demasiado bien los datos de entrenamiento., por lo que no es capaz de generalizar, y cuando le lleguen nuevos datos obtendrá pésimos resultados. \newline  \newline {\bf{Underfitting}} \newline Se produce cuando nuestro modelo no es capaz de identificar patrones. Por lo que tendrá siempre \newline pésimos resultados.}  \tn 
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\mymulticolumn{1}{x{5.377cm}}{Tipos de aprendizaje de datos}  \tn 
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{2.1 ESTADÍSTICA DESCRIPTIVA}}  \tn
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\mymulticolumn{1}{x{5.377cm}}{La estadística descriptiva es un conjunto de técnicas numéricas y gráficas para describir y analizar un grupo de datos, sin extraer conclusiones (inferencias) sobre la población/universo a la que pertenecen. \newline {\bf{En términos generales la estadística descriptiva busca: Describir o Caracterizar un Grupo de Datos.}}}  \tn 
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{5.1 ÁRBOLES DE DECISIÓN}}  \tn
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% That's all folks
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