SEGMENTACIÓN: VINOS
Cecilia Rivas - A01284874, Luis Adrián Mendoza - A00829099
2024-02-19
Contexto
Estos datos son el resultado de un análisis químico de vinos cultivados en la misma región de Italia pero derivados de tres cultivares diferentes.
El análisis determinó las cantidades de 13 componentes que se encuentran en cada uno de
Paso 1. Instalar paquetes y llamar librerías
#install.packages("cluster")
library(cluster)## Warning: package 'cluster' was built under R version 4.3.2#install.packages("ggplot2")
library(ggplot2)## Warning: package 'ggplot2' was built under R version 4.3.2#install.packages("data.table")
library(data.table)
#install.packages("factoextra")
library (factoextra)## Warning: package 'factoextra' was built under R version 4.3.2## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBalibrary(readxl)## Warning: package 'readxl' was built under R version 4.3.2Paso 2. Obtener los datos
df <- read_excel("wine.xlsx")
df_escalada <- scale(df)Paso.3 Cantidad de grupos
grupos<- 3Paso 4. Generar los segmentos
segmentos <- kmeans(df_escalada, grupos)
segmentos## K-means clustering with 3 clusters of sizes 62, 65, 51
##
## Cluster means:
## Alcohol Malic_Acid Ash Ash_Alcanity Magnesium Total_Phenols
## 1 0.8328826 -0.3029551 0.3636801 -0.6084749 0.57596208 0.88274724
## 2 -0.9234669 -0.3929331 -0.4931257 0.1701220 -0.49032869 -0.07576891
## 3 0.1644436 0.8690954 0.1863726 0.5228924 -0.07526047 -0.97657548
## Flavanoids Nonflavanoid_Phenols Proanthocyanins Color_Intensity Hue
## 1 0.97506900 -0.56050853 0.57865427 0.1705823 0.4726504
## 2 0.02075402 -0.03343924 0.05810161 -0.8993770 0.4605046
## 3 -1.21182921 0.72402116 -0.77751312 0.9388902 -1.1615122
## OD280 Proline
## 1 0.7770551 1.1220202
## 2 0.2700025 -0.7517257
## 3 -1.2887761 -0.4059428
##
## Clustering vector:
## [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 3 2 2 2 2 2 2 2 2 2 2 2 1
## [75] 2 2 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [112] 2 2 2 2 2 2 2 3 2 2 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
## [149] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
##
## Within cluster sum of squares by cluster:
## [1] 385.6983 558.6971 326.3537
## (between_SS / total_SS = 44.8 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"Paso 5. Asignar el grupo al que pertenece cada observación
asignacion <- cbind(df, cluster = segmentos$cluster) # pegar a la bd
asignacion## Alcohol Malic_Acid Ash Ash_Alcanity Magnesium Total_Phenols Flavanoids
## 1 14.23 1.71 2.43 15.6 127 2.80 3.06
## 2 13.20 1.78 2.14 11.2 100 2.65 2.76
## 3 13.16 2.36 2.67 18.6 101 2.80 3.24
## 4 14.37 1.95 2.50 16.8 113 3.85 3.49
## 5 13.24 2.59 2.87 21.0 118 2.80 2.69
## 6 14.20 1.76 2.45 15.2 112 3.27 3.39
## 7 14.39 1.87 2.45 14.6 96 2.50 2.52
## 8 14.06 2.15 2.61 17.6 121 2.60 2.51
## 9 14.83 1.64 2.17 14.0 97 2.80 2.98
## 10 13.86 1.35 2.27 16.0 98 2.98 3.15
## 11 14.10 2.16 2.30 18.0 105 2.95 3.32
## 12 14.12 1.48 2.32 16.8 95 2.20 2.43
## 13 13.75 1.73 2.41 16.0 89 2.60 2.76
## 14 14.75 1.73 2.39 11.4 91 3.10 3.69
## 15 14.38 1.87 2.38 12.0 102 3.30 3.64
## 16 13.63 1.81 2.70 17.2 112 2.85 2.91
## 17 14.30 1.92 2.72 20.0 120 2.80 3.14
## 18 13.83 1.57 2.62 20.0 115 2.95 3.40
## 19 14.19 1.59 2.48 16.5 108 3.30 3.93
## 20 13.64 3.10 2.56 15.2 116 2.70 3.03
## 21 14.06 1.63 2.28 16.0 126 3.00 3.17
## 22 12.93 3.80 2.65 18.6 102 2.41 2.41
## 23 13.71 1.86 2.36 16.6 101 2.61 2.88
## 24 12.85 1.60 2.52 17.8 95 2.48 2.37
## 25 13.50 1.81 2.61 20.0 96 2.53 2.61
## 26 13.05 2.05 3.22 25.0 124 2.63 2.68
## 27 13.39 1.77 2.62 16.1 93 2.85 2.94
## 28 13.30 1.72 2.14 17.0 94 2.40 2.19
## 29 13.87 1.90 2.80 19.4 107 2.95 2.97
## 30 14.02 1.68 2.21 16.0 96 2.65 2.33
## 31 13.73 1.50 2.70 22.5 101 3.00 3.25
## 32 13.58 1.66 2.36 19.1 106 2.86 3.19
## 33 13.68 1.83 2.36 17.2 104 2.42 2.69
## 34 13.76 1.53 2.70 19.5 132 2.95 2.74
## 35 13.51 1.80 2.65 19.0 110 2.35 2.53
## 36 13.48 1.81 2.41 20.5 100 2.70 2.98
## 37 13.28 1.64 2.84 15.5 110 2.60 2.68
## 38 13.05 1.65 2.55 18.0 98 2.45 2.43
## 39 13.07 1.50 2.10 15.5 98 2.40 2.64
## 40 14.22 3.99 2.51 13.2 128 3.00 3.04
## 41 13.56 1.71 2.31 16.2 117 3.15 3.29
## 42 13.41 3.84 2.12 18.8 90 2.45 2.68
## 43 13.88 1.89 2.59 15.0 101 3.25 3.56
## 44 13.24 3.98 2.29 17.5 103 2.64 2.63
## 45 13.05 1.77 2.10 17.0 107 3.00 3.00
## 46 14.21 4.04 2.44 18.9 111 2.85 2.65
## 47 14.38 3.59 2.28 16.0 102 3.25 3.17
## 48 13.90 1.68 2.12 16.0 101 3.10 3.39
## 49 14.10 2.02 2.40 18.8 103 2.75 2.92
## 50 13.94 1.73 2.27 17.4 108 2.88 3.54
## 51 13.05 1.73 2.04 12.4 92 2.72 3.27
## 52 13.83 1.65 2.60 17.2 94 2.45 2.99
## 53 13.82 1.75 2.42 14.0 111 3.88 3.74
## 54 13.77 1.90 2.68 17.1 115 3.00 2.79
## 55 13.74 1.67 2.25 16.4 118 2.60 2.90
## 56 13.56 1.73 2.46 20.5 116 2.96 2.78
## 57 14.22 1.70 2.30 16.3 118 3.20 3.00
## 58 13.29 1.97 2.68 16.8 102 3.00 3.23
## 59 13.72 1.43 2.50 16.7 108 3.40 3.67
## 60 12.37 0.94 1.36 10.6 88 1.98 0.57
## 61 12.33 1.10 2.28 16.0 101 2.05 1.09
## 62 12.64 1.36 2.02 16.8 100 2.02 1.41
## 63 13.67 1.25 1.92 18.0 94 2.10 1.79
## 64 12.37 1.13 2.16 19.0 87 3.50 3.10
## 65 12.17 1.45 2.53 19.0 104 1.89 1.75
## 66 12.37 1.21 2.56 18.1 98 2.42 2.65
## 67 13.11 1.01 1.70 15.0 78 2.98 3.18
## 68 12.37 1.17 1.92 19.6 78 2.11 2.00
## 69 13.34 0.94 2.36 17.0 110 2.53 1.30
## 70 12.21 1.19 1.75 16.8 151 1.85 1.28
## 71 12.29 1.61 2.21 20.4 103 1.10 1.02
## 72 13.86 1.51 2.67 25.0 86 2.95 2.86
## 73 13.49 1.66 2.24 24.0 87 1.88 1.84
## 74 12.99 1.67 2.60 30.0 139 3.30 2.89
## 75 11.96 1.09 2.30 21.0 101 3.38 2.14
## 76 11.66 1.88 1.92 16.0 97 1.61 1.57
## 77 13.03 0.90 1.71 16.0 86 1.95 2.03
## 78 11.84 2.89 2.23 18.0 112 1.72 1.32
## 79 12.33 0.99 1.95 14.8 136 1.90 1.85
## 80 12.70 3.87 2.40 23.0 101 2.83 2.55
## 81 12.00 0.92 2.00 19.0 86 2.42 2.26
## 82 12.72 1.81 2.20 18.8 86 2.20 2.53
## 83 12.08 1.13 2.51 24.0 78 2.00 1.58
## 84 13.05 3.86 2.32 22.5 85 1.65 1.59
## 85 11.84 0.89 2.58 18.0 94 2.20 2.21
## 86 12.67 0.98 2.24 18.0 99 2.20 1.94
## 87 12.16 1.61 2.31 22.8 90 1.78 1.69
## 88 11.65 1.67 2.62 26.0 88 1.92 1.61
## 89 11.64 2.06 2.46 21.6 84 1.95 1.69
## 90 12.08 1.33 2.30 23.6 70 2.20 1.59
## 91 12.08 1.83 2.32 18.5 81 1.60 1.50
## 92 12.00 1.51 2.42 22.0 86 1.45 1.25
## 93 12.69 1.53 2.26 20.7 80 1.38 1.46
## 94 12.29 2.83 2.22 18.0 88 2.45 2.25
## 95 11.62 1.99 2.28 18.0 98 3.02 2.26
## 96 12.47 1.52 2.20 19.0 162 2.50 2.27
## 97 11.81 2.12 2.74 21.5 134 1.60 0.99
## 98 12.29 1.41 1.98 16.0 85 2.55 2.50
## 99 12.37 1.07 2.10 18.5 88 3.52 3.75
## 100 12.29 3.17 2.21 18.0 88 2.85 2.99
## 101 12.08 2.08 1.70 17.5 97 2.23 2.17
## 102 12.60 1.34 1.90 18.5 88 1.45 1.36
## 103 12.34 2.45 2.46 21.0 98 2.56 2.11
## 104 11.82 1.72 1.88 19.5 86 2.50 1.64
## 105 12.51 1.73 1.98 20.5 85 2.20 1.92
## 106 12.42 2.55 2.27 22.0 90 1.68 1.84
## 107 12.25 1.73 2.12 19.0 80 1.65 2.03
## 108 12.72 1.75 2.28 22.5 84 1.38 1.76
## 109 12.22 1.29 1.94 19.0 92 2.36 2.04
## 110 11.61 1.35 2.70 20.0 94 2.74 2.92
## 111 11.46 3.74 1.82 19.5 107 3.18 2.58
## 112 12.52 2.43 2.17 21.0 88 2.55 2.27
## 113 11.76 2.68 2.92 20.0 103 1.75 2.03
## 114 11.41 0.74 2.50 21.0 88 2.48 2.01
## 115 12.08 1.39 2.50 22.5 84 2.56 2.29
## 116 11.03 1.51 2.20 21.5 85 2.46 2.17
## 117 11.82 1.47 1.99 20.8 86 1.98 1.60
## 118 12.42 1.61 2.19 22.5 108 2.00 2.09
## 119 12.77 3.43 1.98 16.0 80 1.63 1.25
## 120 12.00 3.43 2.00 19.0 87 2.00 1.64
## 121 11.45 2.40 2.42 20.0 96 2.90 2.79
## 122 11.56 2.05 3.23 28.5 119 3.18 5.08
## 123 12.42 4.43 2.73 26.5 102 2.20 2.13
## 124 13.05 5.80 2.13 21.5 86 2.62 2.65
## 125 11.87 4.31 2.39 21.0 82 2.86 3.03
## 126 12.07 2.16 2.17 21.0 85 2.60 2.65
## 127 12.43 1.53 2.29 21.5 86 2.74 3.15
## 128 11.79 2.13 2.78 28.5 92 2.13 2.24
## 129 12.37 1.63 2.30 24.5 88 2.22 2.45
## 130 12.04 4.30 2.38 22.0 80 2.10 1.75
## 131 12.86 1.35 2.32 18.0 122 1.51 1.25
## 132 12.88 2.99 2.40 20.0 104 1.30 1.22
## 133 12.81 2.31 2.40 24.0 98 1.15 1.09
## 134 12.70 3.55 2.36 21.5 106 1.70 1.20
## 135 12.51 1.24 2.25 17.5 85 2.00 0.58
## 136 12.60 2.46 2.20 18.5 94 1.62 0.66
## 137 12.25 4.72 2.54 21.0 89 1.38 0.47
## 138 12.53 5.51 2.64 25.0 96 1.79 0.60
## 139 13.49 3.59 2.19 19.5 88 1.62 0.48
## 140 12.84 2.96 2.61 24.0 101 2.32 0.60
## 141 12.93 2.81 2.70 21.0 96 1.54 0.50
## 142 13.36 2.56 2.35 20.0 89 1.40 0.50
## 143 13.52 3.17 2.72 23.5 97 1.55 0.52
## 144 13.62 4.95 2.35 20.0 92 2.00 0.80
## 145 12.25 3.88 2.20 18.5 112 1.38 0.78
## 146 13.16 3.57 2.15 21.0 102 1.50 0.55
## 147 13.88 5.04 2.23 20.0 80 0.98 0.34
## 148 12.87 4.61 2.48 21.5 86 1.70 0.65
## 149 13.32 3.24 2.38 21.5 92 1.93 0.76
## 150 13.08 3.90 2.36 21.5 113 1.41 1.39
## 151 13.50 3.12 2.62 24.0 123 1.40 1.57
## 152 12.79 2.67 2.48 22.0 112 1.48 1.36
## 153 13.11 1.90 2.75 25.5 116 2.20 1.28
## 154 13.23 3.30 2.28 18.5 98 1.80 0.83
## 155 12.58 1.29 2.10 20.0 103 1.48 0.58
## 156 13.17 5.19 2.32 22.0 93 1.74 0.63
## 157 13.84 4.12 2.38 19.5 89 1.80 0.83
## 158 12.45 3.03 2.64 27.0 97 1.90 0.58
## 159 14.34 1.68 2.70 25.0 98 2.80 1.31
## 160 13.48 1.67 2.64 22.5 89 2.60 1.10
## 161 12.36 3.83 2.38 21.0 88 2.30 0.92
## 162 13.69 3.26 2.54 20.0 107 1.83 0.56
## 163 12.85 3.27 2.58 22.0 106 1.65 0.60
## 164 12.96 3.45 2.35 18.5 106 1.39 0.70
## 165 13.78 2.76 2.30 22.0 90 1.35 0.68
## 166 13.73 4.36 2.26 22.5 88 1.28 0.47
## 167 13.45 3.70 2.60 23.0 111 1.70 0.92
## 168 12.82 3.37 2.30 19.5 88 1.48 0.66
## 169 13.58 2.58 2.69 24.5 105 1.55 0.84
## 170 13.40 4.60 2.86 25.0 112 1.98 0.96
## 171 12.20 3.03 2.32 19.0 96 1.25 0.49
## 172 12.77 2.39 2.28 19.5 86 1.39 0.51
## 173 14.16 2.51 2.48 20.0 91 1.68 0.70
## 174 13.71 5.65 2.45 20.5 95 1.68 0.61
## 175 13.40 3.91 2.48 23.0 102 1.80 0.75
## 176 13.27 4.28 2.26 20.0 120 1.59 0.69
## 177 13.17 2.59 2.37 20.0 120 1.65 0.68
## 178 14.13 4.10 2.74 24.5 96 2.05 0.76
## Nonflavanoid_Phenols Proanthocyanins Color_Intensity Hue OD280 Proline
## 1 0.28 2.29 5.640000 1.040 3.92 1065
## 2 0.26 1.28 4.380000 1.050 3.40 1050
## 3 0.30 2.81 5.680000 1.030 3.17 1185
## 4 0.24 2.18 7.800000 0.860 3.45 1480
## 5 0.39 1.82 4.320000 1.040 2.93 735
## 6 0.34 1.97 6.750000 1.050 2.85 1450
## 7 0.30 1.98 5.250000 1.020 3.58 1290
## 8 0.31 1.25 5.050000 1.060 3.58 1295
## 9 0.29 1.98 5.200000 1.080 2.85 1045
## 10 0.22 1.85 7.220000 1.010 3.55 1045
## 11 0.22 2.38 5.750000 1.250 3.17 1510
## 12 0.26 1.57 5.000000 1.170 2.82 1280
## 13 0.29 1.81 5.600000 1.150 2.90 1320
## 14 0.43 2.81 5.400000 1.250 2.73 1150
## 15 0.29 2.96 7.500000 1.200 3.00 1547
## 16 0.30 1.46 7.300000 1.280 2.88 1310
## 17 0.33 1.97 6.200000 1.070 2.65 1280
## 18 0.40 1.72 6.600000 1.130 2.57 1130
## 19 0.32 1.86 8.700000 1.230 2.82 1680
## 20 0.17 1.66 5.100000 0.960 3.36 845
## 21 0.24 2.10 5.650000 1.090 3.71 780
## 22 0.25 1.98 4.500000 1.030 3.52 770
## 23 0.27 1.69 3.800000 1.110 4.00 1035
## 24 0.26 1.46 3.930000 1.090 3.63 1015
## 25 0.28 1.66 3.520000 1.120 3.82 845
## 26 0.47 1.92 3.580000 1.130 3.20 830
## 27 0.34 1.45 4.800000 0.920 3.22 1195
## 28 0.27 1.35 3.950000 1.020 2.77 1285
## 29 0.37 1.76 4.500000 1.250 3.40 915
## 30 0.26 1.98 4.700000 1.040 3.59 1035
## 31 0.29 2.38 5.700000 1.190 2.71 1285
## 32 0.22 1.95 6.900000 1.090 2.88 1515
## 33 0.42 1.97 3.840000 1.230 2.87 990
## 34 0.50 1.35 5.400000 1.250 3.00 1235
## 35 0.29 1.54 4.200000 1.100 2.87 1095
## 36 0.26 1.86 5.100000 1.040 3.47 920
## 37 0.34 1.36 4.600000 1.090 2.78 880
## 38 0.29 1.44 4.250000 1.120 2.51 1105
## 39 0.28 1.37 3.700000 1.180 2.69 1020
## 40 0.20 2.08 5.100000 0.890 3.53 760
## 41 0.34 2.34 6.130000 0.950 3.38 795
## 42 0.27 1.48 4.280000 0.910 3.00 1035
## 43 0.17 1.70 5.430000 0.880 3.56 1095
## 44 0.32 1.66 4.360000 0.820 3.00 680
## 45 0.28 2.03 5.040000 0.880 3.35 885
## 46 0.30 1.25 5.240000 0.870 3.33 1080
## 47 0.27 2.19 4.900000 1.040 3.44 1065
## 48 0.21 2.14 6.100000 0.910 3.33 985
## 49 0.32 2.38 6.200000 1.070 2.75 1060
## 50 0.32 2.08 8.900000 1.120 3.10 1260
## 51 0.17 2.91 7.200000 1.120 2.91 1150
## 52 0.22 2.29 5.600000 1.240 3.37 1265
## 53 0.32 1.87 7.050000 1.010 3.26 1190
## 54 0.39 1.68 6.300000 1.130 2.93 1375
## 55 0.21 1.62 5.850000 0.920 3.20 1060
## 56 0.20 2.45 6.250000 0.980 3.03 1120
## 57 0.26 2.03 6.380000 0.940 3.31 970
## 58 0.31 1.66 6.000000 1.070 2.84 1270
## 59 0.19 2.04 6.800000 0.890 2.87 1285
## 60 0.28 0.42 1.950000 1.050 1.82 520
## 61 0.63 0.41 3.270000 1.250 1.67 680
## 62 0.53 0.62 5.750000 0.980 1.59 450
## 63 0.32 0.73 3.800000 1.230 2.46 630
## 64 0.19 1.87 4.450000 1.220 2.87 420
## 65 0.45 1.03 2.950000 1.450 2.23 355
## 66 0.37 2.08 4.600000 1.190 2.30 678
## 67 0.26 2.28 5.300000 1.120 3.18 502
## 68 0.27 1.04 4.680000 1.120 3.48 510
## 69 0.55 0.42 3.170000 1.020 1.93 750
## 70 0.14 2.50 2.850000 1.280 3.07 718
## 71 0.37 1.46 3.050000 0.906 1.82 870
## 72 0.21 1.87 3.380000 1.360 3.16 410
## 73 0.27 1.03 3.740000 0.980 2.78 472
## 74 0.21 1.96 3.350000 1.310 3.50 985
## 75 0.13 1.65 3.210000 0.990 3.13 886
## 76 0.34 1.15 3.800000 1.230 2.14 428
## 77 0.24 1.46 4.600000 1.190 2.48 392
## 78 0.43 0.95 2.650000 0.960 2.52 500
## 79 0.35 2.76 3.400000 1.060 2.31 750
## 80 0.43 1.95 2.570000 1.190 3.13 463
## 81 0.30 1.43 2.500000 1.380 3.12 278
## 82 0.26 1.77 3.900000 1.160 3.14 714
## 83 0.40 1.40 2.200000 1.310 2.72 630
## 84 0.61 1.62 4.800000 0.840 2.01 515
## 85 0.22 2.35 3.050000 0.790 3.08 520
## 86 0.30 1.46 2.620000 1.230 3.16 450
## 87 0.43 1.56 2.450000 1.330 2.26 495
## 88 0.40 1.34 2.600000 1.360 3.21 562
## 89 0.48 1.35 2.800000 1.000 2.75 680
## 90 0.42 1.38 1.740000 1.070 3.21 625
## 91 0.52 1.64 2.400000 1.080 2.27 480
## 92 0.50 1.63 3.600000 1.050 2.65 450
## 93 0.58 1.62 3.050000 0.960 2.06 495
## 94 0.25 1.99 2.150000 1.150 3.30 290
## 95 0.17 1.35 3.250000 1.160 2.96 345
## 96 0.32 3.28 2.600000 1.160 2.63 937
## 97 0.14 1.56 2.500000 0.950 2.26 625
## 98 0.29 1.77 2.900000 1.230 2.74 428
## 99 0.24 1.95 4.500000 1.040 2.77 660
## 100 0.45 2.81 2.300000 1.420 2.83 406
## 101 0.26 1.40 3.300000 1.270 2.96 710
## 102 0.29 1.35 2.450000 1.040 2.77 562
## 103 0.34 1.31 2.800000 0.800 3.38 438
## 104 0.37 1.42 2.060000 0.940 2.44 415
## 105 0.32 1.48 2.940000 1.040 3.57 672
## 106 0.66 1.42 2.700000 0.860 3.30 315
## 107 0.37 1.63 3.400000 1.000 3.17 510
## 108 0.48 1.63 3.300000 0.880 2.42 488
## 109 0.39 2.08 2.700000 0.860 3.02 312
## 110 0.29 2.49 2.650000 0.960 3.26 680
## 111 0.24 3.58 2.900000 0.750 2.81 562
## 112 0.26 1.22 2.000000 0.900 2.78 325
## 113 0.60 1.05 3.800000 1.230 2.50 607
## 114 0.42 1.44 3.080000 1.100 2.31 434
## 115 0.43 1.04 2.900000 0.930 3.19 385
## 116 0.52 2.01 1.900000 1.710 2.87 407
## 117 0.30 1.53 1.950000 0.950 3.33 495
## 118 0.34 1.61 2.060000 1.060 2.96 345
## 119 0.43 0.83 3.400000 0.700 2.12 372
## 120 0.37 1.87 1.280000 0.930 3.05 564
## 121 0.32 1.83 3.250000 0.800 3.39 625
## 122 0.47 1.87 6.000000 0.930 3.69 465
## 123 0.43 1.71 2.080000 0.920 3.12 365
## 124 0.30 2.01 2.600000 0.730 3.10 380
## 125 0.21 2.91 2.800000 0.750 3.64 380
## 126 0.37 1.35 2.760000 0.860 3.28 378
## 127 0.39 1.77 3.940000 0.690 2.84 352
## 128 0.58 1.76 3.000000 0.970 2.44 466
## 129 0.40 1.90 2.120000 0.890 2.78 342
## 130 0.42 1.35 2.600000 0.790 2.57 580
## 131 0.21 0.94 4.100000 0.760 1.29 630
## 132 0.24 0.83 5.400000 0.740 1.42 530
## 133 0.27 0.83 5.700000 0.660 1.36 560
## 134 0.17 0.84 5.000000 0.780 1.29 600
## 135 0.60 1.25 5.450000 0.750 1.51 650
## 136 0.63 0.94 7.100000 0.730 1.58 695
## 137 0.53 0.80 3.850000 0.750 1.27 720
## 138 0.63 1.10 5.000000 0.820 1.69 515
## 139 0.58 0.88 5.700000 0.810 1.82 580
## 140 0.53 0.81 4.920000 0.890 2.15 590
## 141 0.53 0.75 4.600000 0.770 2.31 600
## 142 0.37 0.64 5.600000 0.700 2.47 780
## 143 0.50 0.55 4.350000 0.890 2.06 520
## 144 0.47 1.02 4.400000 0.910 2.05 550
## 145 0.29 1.14 8.210000 0.650 2.00 855
## 146 0.43 1.30 4.000000 0.600 1.68 830
## 147 0.40 0.68 4.900000 0.580 1.33 415
## 148 0.47 0.86 7.650000 0.540 1.86 625
## 149 0.45 1.25 8.420000 0.550 1.62 650
## 150 0.34 1.14 9.400000 0.570 1.33 550
## 151 0.22 1.25 8.600000 0.590 1.30 500
## 152 0.24 1.26 10.800000 0.480 1.47 480
## 153 0.26 1.56 7.100000 0.610 1.33 425
## 154 0.61 1.87 10.520000 0.560 1.51 675
## 155 0.53 1.40 7.600000 0.580 1.55 640
## 156 0.61 1.55 7.900000 0.600 1.48 725
## 157 0.48 1.56 9.010000 0.570 1.64 480
## 158 0.63 1.14 7.500000 0.670 1.73 880
## 159 0.53 2.70 13.000000 0.570 1.96 660
## 160 0.52 2.29 11.750000 0.570 1.78 620
## 161 0.50 1.04 7.650000 0.560 1.58 520
## 162 0.50 0.80 5.880000 0.960 1.82 680
## 163 0.60 0.96 5.580000 0.870 2.11 570
## 164 0.40 0.94 5.280000 0.680 1.75 675
## 165 0.41 1.03 9.580000 0.700 1.68 615
## 166 0.52 1.15 6.620000 0.780 1.75 520
## 167 0.43 1.46 10.680000 0.850 1.56 695
## 168 0.40 0.97 10.260000 0.720 1.75 685
## 169 0.39 1.54 8.660000 0.740 1.80 750
## 170 0.27 1.11 8.500000 0.670 1.92 630
## 171 0.40 0.73 5.500000 0.660 1.83 510
## 172 0.48 0.64 9.899999 0.570 1.63 470
## 173 0.44 1.24 9.700000 0.620 1.71 660
## 174 0.52 1.06 7.700000 0.640 1.74 740
## 175 0.43 1.41 7.300000 0.700 1.56 750
## 176 0.43 1.35 10.200000 0.590 1.56 835
## 177 0.53 1.46 9.300000 0.600 1.62 840
## 178 0.56 1.35 9.200000 0.610 1.60 560
## cluster
## 1 1
## 2 1
## 3 1
## 4 1
## 5 1
## 6 1
## 7 1
## 8 1
## 9 1
## 10 1
## 11 1
## 12 1
## 13 1
## 14 1
## 15 1
## 16 1
## 17 1
## 18 1
## 19 1
## 20 1
## 21 1
## 22 1
## 23 1
## 24 1
## 25 1
## 26 1
## 27 1
## 28 1
## 29 1
## 30 1
## 31 1
## 32 1
## 33 1
## 34 1
## 35 1
## 36 1
## 37 1
## 38 1
## 39 1
## 40 1
## 41 1
## 42 1
## 43 1
## 44 1
## 45 1
## 46 1
## 47 1
## 48 1
## 49 1
## 50 1
## 51 1
## 52 1
## 53 1
## 54 1
## 55 1
## 56 1
## 57 1
## 58 1
## 59 1
## 60 2
## 61 2
## 62 3
## 63 2
## 64 2
## 65 2
## 66 2
## 67 2
## 68 2
## 69 2
## 70 2
## 71 2
## 72 2
## 73 2
## 74 1
## 75 2
## 76 2
## 77 2
## 78 2
## 79 2
## 80 2
## 81 2
## 82 2
## 83 2
## 84 3
## 85 2
## 86 2
## 87 2
## 88 2
## 89 2
## 90 2
## 91 2
## 92 2
## 93 2
## 94 2
## 95 2
## 96 1
## 97 2
## 98 2
## 99 2
## 100 2
## 101 2
## 102 2
## 103 2
## 104 2
## 105 2
## 106 2
## 107 2
## 108 2
## 109 2
## 110 2
## 111 2
## 112 2
## 113 2
## 114 2
## 115 2
## 116 2
## 117 2
## 118 2
## 119 3
## 120 2
## 121 2
## 122 1
## 123 2
## 124 2
## 125 2
## 126 2
## 127 2
## 128 2
## 129 2
## 130 2
## 131 3
## 132 3
## 133 3
## 134 3
## 135 3
## 136 3
## 137 3
## 138 3
## 139 3
## 140 3
## 141 3
## 142 3
## 143 3
## 144 3
## 145 3
## 146 3
## 147 3
## 148 3
## 149 3
## 150 3
## 151 3
## 152 3
## 153 3
## 154 3
## 155 3
## 156 3
## 157 3
## 158 3
## 159 3
## 160 3
## 161 3
## 162 3
## 163 3
## 164 3
## 165 3
## 166 3
## 167 3
## 168 3
## 169 3
## 170 3
## 171 3
## 172 3
## 173 3
## 174 3
## 175 3
## 176 3
## 177 3
## 178 3Paso 6. Graficar los clusters
fviz_cluster(segmentos, data = df_escalada)
Paso 7. Optimizar la cantidad de grupos
La cantidad optima de grupos corresponde al punto más alto de la siguiente gráfica
set.seed (123)
optimizacion <- clusGap(df_escalada, FUN = kmeans, nstart=1,K.max = 10)
plot(optimizacion, xlab = "Número de clusters k")
Paso 8. Comparar segmentos
promedio_original <- aggregate(asignacion, by=list(asignacion$cluster), FUN=mean)
promedio_original## Group.1 Alcohol Malic_Acid Ash Ash_Alcanity Magnesium Total_Phenols
## 1 1 13.67677 1.997903 2.466290 17.46290 107.96774 2.847581
## 2 2 12.25092 1.897385 2.231231 20.06308 92.73846 2.247692
## 3 3 13.13412 3.307255 2.417647 21.24118 98.66667 1.683922
## Flavanoids Nonflavanoid_Phenols Proanthocyanins Color_Intensity Hue
## 1 3.0032258 0.2920968 1.922097 5.453548 1.0654839
## 2 2.0500000 0.3576923 1.624154 2.973077 1.0627077
## 3 0.8188235 0.4519608 1.145882 7.234706 0.6919608
## OD280 Proline cluster
## 1 3.163387 1100.2258 1
## 2 2.803385 510.1692 2
## 3 1.696667 619.0588 3Conclusión
La división de clusters de los vinos se calculó de acuerdo a sus cantidades de alcohol, ácido málico, magnesio, entre otras características.
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