Package 'discoveR'

Title: Exploratory Data Analysis System
Description: Performs an exploratory data analysis through a 'shiny' interface. It includes basic methods such as the mean, median, mode, normality test, among others. It also includes clustering techniques such as Principal Components Analysis, Hierarchical Clustering and the K-Means Method.
Authors: Oldemar Rodriguez [aut, cre], Diego Jiménez [aut]
Maintainer: Oldemar Rodriguez <[email protected]>
License: GPL (>= 2)
Version: 3.1.2
Built: 2024-12-03 07:00:11 UTC
Source: CRAN

Help Index


Calculate inter-class inertia

Description

Calculate inter-class inertia

Usage

BP(DF, clusters)

Arguments

DF

a data.frame object.

clusters

a vector specifying the cluster of each individual.

Value

numeric

Author(s)

Diego Jimenez <[email protected]>

Examples

m <- hclust(dist(iris[, -5]))
BP(iris[, -5], cutree(m, 3))

Calculation of the center of clusters

Description

Calculation of the center of clusters

Usage

calc.centros(data, clusters)

Arguments

data

a data.frame object.

clusters

a vector specifying the cluster of each individual.

Value

list

Author(s)

Diego Jimenez <[email protected]>

Examples

clusters <- factor(kmeans(iris[, -5], 3)$cluster)
calc.centros(iris[, -5], clusters)

Exploratory Data Analysis System

Description

Performs an exploratory data analysis through a 'shiny' interface. It includes basic methods such as the mean, median, mode, normality test, among others. It also includes clustering techniques such as Principal Components Analysis, Hierarchical Clustering and the K-Means Method.

Details

Package: discoveR
Type: Package
Version: 3.1.2
Date: 2023-01-18
License: GPL (>=2)

Author(s)

Maintainer: Oldemar Rodriguez Rojas <[email protected]>


AFC biplot

Description

AFC biplot

Usage

e_afcbi(
  modelo,
  axes = c(1, 2),
  colorRow = "steelblue",
  colorCol = "forestgreen",
  cos2Row = 0,
  cos2Col = 0,
  colorRowCos = "firebrick",
  colorColCos = "darkorchid",
  titulos = c("Bien Representados", "Mal Representados"),
  etq = T
)

Arguments

modelo

an object of class CA [FactoMineR].

axes

a numeric vector of length 2 specifying the dimensions to be plotted.

colorRow

a color for the individuals well represented.

colorCol

a color for the variables well represented.

cos2Row

a numeric value from 0 to 1 specifying the quality of the individuals.

cos2Col

a numeric value from 0 to 1 specifying the quality of the variables.

colorRowCos

a color for the individuals badly represented.

colorColCos

a color for the variables badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::CA(iris[, -5], graph = FALSE)
e_afcbi(p)

AFC biplot in 3D

Description

AFC biplot in 3D

Usage

e_afcbi_3D(
  modelo,
  axes = c(1, 2, 3),
  colorRow = "steelblue",
  colorCol = "forestgreen",
  cos2Row = 0,
  cos2Col = 0,
  colorRowCos = "firebrick",
  colorColCos = "darkorchid",
  titulos = c("Bien Representados", "Mal Representados"),
  etq = T
)

Arguments

modelo

an object of class CA [FactoMineR].

axes

a numeric vector of length 3 specifying the dimensions to be plotted.

colorRow

a color for the individuals well represented.

colorCol

a color for the variables well represented.

cos2Row

a numeric value from 0 to 1 specifying the quality of the individuals.

cos2Col

a numeric value from 0 to 1 specifying the quality of the variables.

colorRowCos

a color for individuals badly represented.

colorColCos

a color for variables badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::CA(iris[, -5], graph = FALSE)
e_afcbi_3D(p)

AFC plot of variables

Description

AFC plot of variables

Usage

e_afccol(
  modelo,
  axes = c(1, 2),
  colorCol = "forestgreen",
  cos2 = 0,
  colorCos = "darkorchid",
  titulos = c("Bien Representados", "Mal Representados")
)

Arguments

modelo

an object of class CA [FactoMineR].

axes

a numeric vector of length 2 specifying the dimensions to be plotted.

colorCol

a color for the variables well represented.

cos2

a numeric value from 0 to 1 specifying the quality of the variables.

colorCos

a color for the variables badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::CA(iris[, -5], graph = FALSE)
e_afccol(p)

AFC plot of variables in 3D

Description

AFC plot of variables in 3D

Usage

e_afccol_3D(
  modelo,
  axes = c(1, 2, 3),
  colorCol = "forestgreen",
  cos2 = 0,
  colorCos = "darkorchid",
  titulos = c("Bien Representados", "Mal Representados")
)

Arguments

modelo

an object of class CA [FactoMineR].

axes

a numeric vector of length 3 specifying the dimensions to be plotted.

colorCol

a color for the variables well represented.

cos2

a numeric value from 0 to 1 specifying the quality of the variables.

colorCos

a color for variables badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::CA(iris[, -5], graph = FALSE)
e_afccol_3D(p)

AFCM biplot

Description

AFCM biplot

Usage

e_afcmbi(
  modelo,
  axes = c(1, 2),
  colorInd = "steelblue",
  colorVar = "forestgreen",
  cos2Ind = 0,
  cos2Var = 0,
  colorIndCos = "firebrick",
  colorVarCos = "darkorchid",
  titulos = c("Bien Representados", "Mal Representados"),
  etq = T
)

Arguments

modelo

an object of class AFCM [FactoMineR].

axes

a numeric vector of length 2 specifying the dimensions to be plotted.

colorInd

a color for the individuals well represented.

colorVar

a color for the variables well represented.

cos2Ind

a numeric value from 0 to 1 specifying the quality of the individuals.

cos2Var

a numeric value from 0 to 1 specifying the quality of the variables.

colorIndCos

a color for the individuals badly represented.

colorVarCos

a color for the variables badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmbi(p)

AFCM biplot in 3D

Description

AFCM biplot in 3D

Usage

e_afcmbi_3D(
  modelo,
  axes = c(1, 2, 3),
  colorInd = "steelblue",
  colorVar = "forestgreen",
  cos2Ind = 0,
  cos2Var = 0,
  colorIndCos = "firebrick",
  colorVarCos = "darkorchid",
  titulos = c("Bien Representados", "Mal Representados"),
  etq = T
)

Arguments

modelo

an object of class AFCM [FactoMineR].

axes

a numeric vector of length 3 specifying the dimensions to be plotted.

colorInd

a color for the individuals well represented.

colorVar

a color for the variables well represented.

cos2Ind

a numeric value from 0 to 1 specifying the quality of the individuals.

cos2Var

a numeric value from 0 to 1 specifying the quality of the variables.

colorIndCos

a color for individuals badly represented.

colorVarCos

a color for variables badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmbi_3D(p)

AFCM plot of categories

Description

AFCM plot of categories

Usage

e_afcmcat(
  modelo,
  axes = c(1, 2),
  colorCat = "forestgreen",
  cos2 = 0,
  colorCos = "darkorchid",
  titulos = c("Bien Representados", "Mal Representados")
)

Arguments

modelo

an object of class AFCM [FactoMineR].

axes

a numeric vector of length 2 specifying the dimensions to be plotted.

colorCat

a color for the categories well represented.

cos2

a numeric value from 0 to 1 specifying the quality of the categories.

colorCos

a color for the categories badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmcat(p)

AFCM plot of categories in 3D

Description

AFCM plot of categories in 3D

Usage

e_afcmcat_3D(
  modelo,
  axes = c(1, 2, 3),
  colorCat = "forestgreen",
  cos2 = 0,
  colorCos = "darkorchid",
  titulos = c("Bien Representados", "Mal Representados")
)

Arguments

modelo

an object of class AFCM [FactoMineR].

axes

a numeric vector of length 3 specifying the dimensions to be plotted.

colorCat

a color for the categories well represented.

cos2

a numeric value from 0 to 1 specifying the quality of the categories.

colorCos

a color for categories badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmcat_3D(p)

AFCM plot of individuals

Description

AFCM plot of individuals

Usage

e_afcmind(
  modelo,
  axes = c(1, 2),
  colorInd = "steelblue",
  cos2 = 0,
  colorCos = "firebrick",
  titulos = c("Bien Representados", "Mal Representados"),
  etq = T
)

Arguments

modelo

an object of class AFCM [FactoMineR].

axes

a numeric vector of length 2 specifying the dimensions to be plotted.

colorInd

a color for the individuals well represented.

cos2

a numeric value from 0 to 1 specifying the quality of the individuals.

colorCos

a color for individuals badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmind(p)

AFCM plot of individuals in 3D

Description

AFCM plot of individuals in 3D

Usage

e_afcmind_3D(
  modelo,
  axes = c(1, 2, 3),
  colorInd = "steelblue",
  cos2 = 0,
  colorCos = "firebrick",
  titulos = c("Bien Representados", "Mal Representados"),
  etq = T
)

Arguments

modelo

an object of class AFCM [FactoMineR].

axes

a numeric vector of length 3 specifying the dimensions to be plotted.

colorInd

a color for the individuals well represented.

cos2

a numeric value from 0 to 1 specifying the quality of the individuals.

colorCos

a color for individuals badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmind_3D(p)

AFCM plot of variables

Description

AFCM plot of variables

Usage

e_afcmvar(modelo, axes = c(1, 2), colorVar = "forestgreen")

Arguments

modelo

an object of class AFCM [FactoMineR].

axes

a numeric vector of length 2 specifying the dimensions to be plotted.

colorVar

a color for the variables.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmvar(p)

AFCM plot of variables in 3D

Description

AFCM plot of variables in 3D

Usage

e_afcmvar_3D(modelo, axes = c(1, 2, 3), colorVar = "forestgreen")

Arguments

modelo

an object of class AFCM [FactoMineR].

axes

a numeric vector of length 3 specifying the dimensions to be plotted.

colorVar

a color for the variables well represented.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmvar_3D(p)

AFC plot of individuals

Description

AFC plot of individuals

Usage

e_afcrow(
  modelo,
  axes = c(1, 2),
  colorRow = "steelblue",
  cos2 = 0,
  colorCos = "firebrick",
  titulos = c("Bien Representados", "Mal Representados"),
  etq = T
)

Arguments

modelo

an object of class CA [FactoMineR].

axes

a numeric vector of length 2 specifying the dimensions to be plotted.

colorRow

a color for the individuals well represented.

cos2

a numeric value from 0 to 1 specifying the quality of the individuals.

colorCos

a color for individuals badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::CA(iris[, -5], graph = FALSE)
e_afcrow(p)

AFC plot of individuals in 3D

Description

AFC plot of individuals in 3D

Usage

e_afcrow_3D(
  modelo,
  axes = c(1, 2, 3),
  colorRow = "steelblue",
  cos2 = 0,
  colorCos = "firebrick",
  titulos = c("Bien Representados", "Mal Representados"),
  etq = T
)

Arguments

modelo

an object of class CA [FactoMineR].

axes

a numeric vector of length 3 specifying the dimensions to be plotted.

colorRow

a color for the individuals well represented.

cos2

a numeric value from 0 to 1 specifying the quality of the individuals.

colorCos

a color for individuals badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::CA(iris[, -5], graph = FALSE)
e_afcrow_3D(p)

Balloonplot

Description

Balloonplot

Usage

e_balloon(datos)

Arguments

datos

a data frame object.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

e_balloon(iris)

Barplot for categoric variable by clusters.

Description

Barplot for categoric variable by clusters.

Usage

e_cat(clusters, var, colores = NULL, escalar = T)

Arguments

clusters

a vector specifying the cluster of each individual.

var

a factor column of a data.frame.

colores

a vector of color for each cluster.

escalar

a boolean value specifying if use percentage or real values.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

clusters <- factor(kmeans(iris[, -5], 3)$cluster)
e_cat(clusters, iris[, 5], colores = c("steelblue", "pink", "forestgreen"))

Horizontal representation for centers of clusters.

Description

Horizontal representation for centers of clusters.

Usage

e_horiz(centros, colores = NULL)

Arguments

centros

a data.frame object with the centers of the clusters.

colores

a vector of color for each cluster.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

clusters <- factor(kmeans(iris[, -5], 3)$cluster)
c <- calc.centros(iris[, -5], clusters)
e_horiz(c$real, c("steelblue", "pink", "forestgreen"))

Inertia plot of clusterization

Description

Inertia plot of clusterization

Usage

e_inercia(
  data,
  titulos = c("Inercia", "Inercia Inter-Clase", "Inercia Inter-Clase")
)

Arguments

data

a data.frame object with the inertia values.

titulos

a character vector of length 3 specifying the titles to use on legend.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>


Jambu Elbow plot

Description

Jambu Elbow plot

Usage

e_jambu(data, max.clusters)

Arguments

data

a data.frame object.

max.clusters

a numeric value specifying the number of times to generate the model.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

e_jambu(iris[, -5], 10)

PCA plot of individuals colored by clusters

Description

PCA plot of individuals colored by clusters

Usage

e_mapa(pca.model, clusters, colores = NULL, ejes = c(1, 2), etq = F)

Arguments

pca.model

an object of class PCA [FactoMineR].

clusters

a vector specifying the cluster of each individual.

colores

a vector of color for each cluster.

ejes

a numeric vector of length 2 specifying the dimensions to be plotted.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
clusters <- factor(kmeans(iris[, -5], 3)$cluster)
e_mapa(p, clusters, c("steelblue", "pink", "forestgreen"), etq = FALSE)

PCA plot of individuals colored by clusters

Description

PCA plot of individuals colored by clusters

Usage

e_mapa_3D(pca.model, clusters, colores = NULL, ejes = c(1, 2, 3), etq = F)

Arguments

pca.model

an object of class PCA [FactoMineR].

clusters

a vector specifying the cluster of each individual.

colores

a vector of color for each cluster.

ejes

a numeric vector of length 3 specifying the dimensions to be plotted.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
clusters <- factor(kmeans(iris[, -5], 3)$cluster)
e_mapa_3D(p, clusters, c("steelblue", "pink", "forestgreen"), etq = FALSE)

PCA biplot

Description

PCA biplot

Usage

e_pcabi(
  modelo,
  axes = c(1, 2),
  colorInd = "steelblue",
  colorVar = "forestgreen",
  cos2Ind = 0,
  cos2Var = 0,
  colorIndCos = "firebrick",
  colorVarCos = "darkorchid",
  titulos = c("Bien Representados", "Mal Representados"),
  etq = F
)

Arguments

modelo

an object of class PCA [FactoMineR].

axes

a numeric vector of length 2 specifying the dimensions to be plotted.

colorInd

a color for the individuals well represented.

colorVar

a color for the variables well represented.

cos2Ind

a numeric value from 0 to 1 specifying the quality of the individuals.

cos2Var

a numeric value from 0 to 1 specifying the quality of the variables.

colorIndCos

a color for the individuals badly represented.

colorVarCos

a color for the variables badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
e_pcabi(p)

PCA biplot in 3D

Description

PCA biplot in 3D

Usage

e_pcabi_3D(
  modelo,
  axes = c(1, 2, 3),
  colorInd = "steelblue",
  colorVar = "forestgreen",
  cos2Ind = 0,
  cos2Var = 0,
  colorIndCos = "firebrick",
  colorVarCos = "darkorchid",
  titulos = c("Bien Representados", "Mal Representados"),
  etq = F
)

Arguments

modelo

an object of class PCA [FactoMineR].

axes

a numeric vector of length 3 specifying the dimensions to be plotted.

colorInd

a color for the individuals well represented.

colorVar

a color for the variables well represented.

cos2Ind

a numeric value from 0 to 1 specifying the quality of the individuals.

cos2Var

a numeric value from 0 to 1 specifying the quality of the variables.

colorIndCos

a color for individuals badly represented.

colorVarCos

a color for variables badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
e_pcabi_3D(p)

PCA plot of individuals

Description

PCA plot of individuals

Usage

e_pcaind(
  modelo,
  axes = c(1, 2),
  colorInd = "steelblue",
  cos2 = 0,
  colorCos = "firebrick",
  titulos = c("Bien Representados", "Mal Representados"),
  etq = F
)

Arguments

modelo

an object of class PCA [FactoMineR].

axes

a numeric vector of length 2 specifying the dimensions to be plotted.

colorInd

a color for the individuals well represented.

cos2

a numeric value from 0 to 1 specifying the quality of the individuals.

colorCos

a color for individuals badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
e_pcaind(p)

PCA plot of individuals in 3D

Description

PCA plot of individuals in 3D

Usage

e_pcaind_3D(
  modelo,
  axes = c(1, 2, 3),
  colorInd = "steelblue",
  cos2 = 0,
  colorCos = "firebrick",
  titulos = c("Bien Representados", "Mal Representados"),
  etq = F
)

Arguments

modelo

an object of class PCA [FactoMineR].

axes

a numeric vector of length 3 specifying the dimensions to be plotted.

colorInd

a color for the individuals well represented.

cos2

a numeric value from 0 to 1 specifying the quality of the individuals.

colorCos

a color for individuals badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

etq

a boolean, whether to add label to graph or not.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
e_pcaind_3D(p)

PCA plot of variables

Description

PCA plot of variables

Usage

e_pcavar(
  modelo,
  axes = c(1, 2),
  colorVar = "forestgreen",
  cos2 = 0,
  colorCos = "darkorchid",
  titulos = c("Bien Representados", "Mal Representados")
)

Arguments

modelo

an object of class PCA [FactoMineR].

axes

a numeric vector of length 2 specifying the dimensions to be plotted.

colorVar

a color for the variables well represented.

cos2

a numeric value from 0 to 1 specifying the quality of the variables.

colorCos

a color for the variables badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
e_pcavar(p)

PCA plot of variables in 3D

Description

PCA plot of variables in 3D

Usage

e_pcavar_3D(
  modelo,
  axes = c(1, 2, 3),
  colorVar = "forestgreen",
  cos2 = 0,
  colorCos = "darkorchid",
  titulos = c("Bien Representados", "Mal Representados")
)

Arguments

modelo

an object of class PCA [FactoMineR].

axes

a numeric vector of length 3 specifying the dimensions to be plotted.

colorVar

a color for the variables well represented.

cos2

a numeric value from 0 to 1 specifying the quality of the variables.

colorCos

a color for variables badly represented.

titulos

a character vector of length 2 specifying the titles to use on legend.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
e_pcavar_3D(p)

Radar representation for centers of clusters.

Description

Radar representation for centers of clusters.

Usage

e_radar(centros, colores = NULL)

Arguments

centros

a data.frame object with the centers of the clusters.

colores

a vector of color for each cluster.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

clusters <- factor(kmeans(iris[, -5], 3)$cluster)
c <- calc.centros(iris[, -5], clusters)
e_radar(c$porcentual, c("steelblue", "pink", "forestgreen"))

Silhouette plot

Description

Silhouette plot

Usage

e_silhouette(data, max.clusters)

Arguments

data

a data.frame object.

max.clusters

a numeric value specifying the number of times to generate the model.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

e_silhouette(iris[, -5], 10)

Vertical representation for centers of clusters.

Description

Vertical representation for centers of clusters.

Usage

e_vert(centros, colores = NULL)

Arguments

centros

a data.frame object with the centers of the clusters.

colores

a vector of color for each cluster.

Value

echarts4r plot

Author(s)

Diego Jimenez <[email protected]>

Examples

clusters <- factor(kmeans(iris[, -5], 3)$cluster)
c <- calc.centros(iris[, -5], clusters)
e_vert(c$real, c("steelblue", "pink", "forestgreen"))

Dendrogram plot

Description

Dendrogram plot

Usage

gg_dendrograma(model, k, colors = NULL)

Arguments

model

an object of class hclust.

k

a vector specifying the cluster of each individual.

colors

a vector of color for each cluster.

Value

ggplot

Author(s)

Diego Jimenez <[email protected]>


Calculate total inertia

Description

Calculate total inertia

Usage

inercia.total(DF)

Arguments

DF

a data.frame object.

Value

numeric

Author(s)

Diego Jimenez <[email protected]>


Run the Shiny Application

Description

Run the Shiny Application

Usage

run_app(...)

Arguments

...

A series of options to be used inside the app.

Examples

if(interactive()) {
  run_app()
}

Calculate intra-class inertia

Description

Calculate intra-class inertia

Usage

WP(DF, clusters)

Arguments

DF

a data.frame object.

clusters

a vector specifying the cluster of each individual.

Value

numeric

Author(s)

Diego Jimenez <[email protected]>

Examples

m <- hclust(dist(iris[, -5]))
WP(iris[, -5], cutree(m, 3))