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Técnicas de reducción de la dimensionalidad

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Técnicas de reducción de la dimensionalidad

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About this activity

Filtrado y envoltura en DR

Created by

Adolfo Moya
Adolfo Moya
Ecuador

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Técnicas de reducción de la dimensionalidad
 

Técnicas de reducción de la dimensionalidadOnline version

Filtrado y envoltura en DR

by Adolfo Moya
1

¿Qué caracteriza una técnica de filtrado en reducción de dimensionalidad?

2

Ejemplo clásico de método de filtrado?

3

¿Qué implica un wrapper en DR?

4

Ventaja principal de los wrappers?

5

Desventaja típica de wrappers?

6

¿Qué es Sequential Forward Selection (SFS)?

7

¿Qué es Sequential Backward Elimination (SBE)?

8

¿Qué evalúa el filtro chi-cuadrado en selección de características?

9

ReliefF es un método de...

10

¿Cuál de estos es puramente wrapper?

Explicación

Filtrado usa medidas como varianza o chi-cuadrado sin entrenar modelos.

La filtración por varianza alta es un ejemplo típico de filtro.

Los wrappers evalúan rendimiento de un modelo con diferentes subconjuntos.

Son muy precisos pero suelen ser costosos computacionalmente.

Evaluar muchos subconjuntos implica mucho tiempo de cómputo.

SFS empieza con ninguna y agrega una a la vez, buscando mejora.

SBE empieza con todas y elimina una a la vez.

Chi-cuadrado mide dependencia entre característica y etiqueta.

ReliefF asigna puntuaciones a características sin usar modelo.

RFE evalúa iterativamente combinaciones usando un modelo.

 
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