АД_ЛР2_N1
Лекомцева Ангелина
2026-02-16
Задание 1. Разведочный анализ с пакетом caret
library(caret)
set.seed(123)Генерация данных
x <- matrix(rnorm(50*5), ncol=5)
y <- factor(rep(c("A","B"), 25))
colnames(x) <- paste0("Var",1:5)Матрица диаграмм рассеяния
featurePlot(x = x, y = y, plot = "pairs")
Boxplot
featurePlot(x = x, y = y, plot = "box")
Вывод: признаки случайные, классы не разделяются.
Задание 2. Важность признаков (FSelector, iris)
library(FSelector)
data(iris)Расчёт информационного прироста
weights <- information.gain(Species ~ ., data = iris)
weights## attr_importance
## Sepal.Length 0.4521286
## Sepal.Width 0.2672750
## Petal.Length 0.9402853
## Petal.Width 0.9554360Визуализация
library(ggplot2)
weights_df <- as.data.frame(weights)
weights_df$Feature <- rownames(weights_df)
ggplot(weights_df,
aes(x = reorder(Feature, attr_importance),
y = attr_importance)) +
geom_bar(stat="identity", fill="steelblue") +
coord_flip() +
xlab("Признак") +
ylab("Важность")
Вывод: Petal.Length и Petal.Width наиболее информативны.
Задание 3. Дискретизация (arules)
library(arules)## Загрузка требуемого пакета: Matrix##
## Присоединяю пакет: 'arules'## Следующие объекты скрыты от 'package:base':
##
## abbreviate, writeInterval
interval_disc <- discretize(iris$Petal.Length,
method="interval",
categories=3)## Warning in discretize(iris$Petal.Length, method = "interval", categories = 3):
## Parameter categories is deprecated. Use breaks instead! Also, the default
## method is now frequency!table(interval_disc)## interval_disc
## [1,2.97) [2.97,4.93) [4.93,6.9]
## 50 54 46Frequency
freq_disc <- discretize(iris$Petal.Length,
method="frequency",
categories=3)## Warning in discretize(iris$Petal.Length, method = "frequency", categories = 3):
## Parameter categories is deprecated. Use breaks instead! Also, the default
## method is now frequency!table(freq_disc)## freq_disc
## [1,2.63) [2.63,4.9) [4.9,6.9]
## 50 49 51Cluster
cluster_disc <- discretize(iris$Petal.Length,
method="cluster",
categories=3)## Warning in discretize(iris$Petal.Length, method = "cluster", categories = 3):
## Parameter categories is deprecated. Use breaks instead! Also, the default
## method is now frequency!table(cluster_disc)## cluster_disc
## [1,2.85) [2.85,4.89) [4.89,6.9]
## 50 49 51Fixed
fixed_disc <- discretize(iris$Petal.Length,
method="fixed",
breaks=c(0,2.5,5,8))
table(fixed_disc)## fixed_disc
## [0,2.5) [2.5,5) [5,8]
## 50 54 46Вывод: разные методы дают разное распределение категорий.
Задание 4. Boruta (Ozone)
library(Boruta)
library(mlbench)
data(Ozone)
Ozone <- na.omit(Ozone)
set.seed(123)Запуск Boruta
boruta_result <- Boruta(V1 ~ ., data=Ozone, doTrace=2)## 1. run of importance source...## 2. run of importance source...## 3. run of importance source...## 4. run of importance source...## 5. run of importance source...## 6. run of importance source...## 7. run of importance source...## 8. run of importance source...## 9. run of importance source...## 10. run of importance source...## 11. run of importance source...## After 11 iterations, +0.92 secs:## confirmed 10 attributes: V11, V12, V13, V2, V4 and 5 more;## rejected 1 attribute: V3;## still have 1 attribute left.## 12. run of importance source...## 13. run of importance source...## 14. run of importance source...## 15. run of importance source...## 16. run of importance source...## 17. run of importance source...## 18. run of importance source...## 19. run of importance source...## 20. run of importance source...## 21. run of importance source...## 22. run of importance source...## 23. run of importance source...## 24. run of importance source...## 25. run of importance source...## 26. run of importance source...## 27. run of importance source...## 28. run of importance source...## 29. run of importance source...## 30. run of importance source...## 31. run of importance source...## 32. run of importance source...## 33. run of importance source...## 34. run of importance source...## 35. run of importance source...## 36. run of importance source...## 37. run of importance source...## 38. run of importance source...## 39. run of importance source...## 40. run of importance source...## 41. run of importance source...## 42. run of importance source...## 43. run of importance source...## 44. run of importance source...## 45. run of importance source...## 46. run of importance source...## 47. run of importance source...## 48. run of importance source...## 49. run of importance source...## 50. run of importance source...## 51. run of importance source...## 52. run of importance source...## 53. run of importance source...## 54. run of importance source...## 55. run of importance source...## 56. run of importance source...## 57. run of importance source...## 58. run of importance source...## 59. run of importance source...## 60. run of importance source...## 61. run of importance source...## 62. run of importance source...## 63. run of importance source...## 64. run of importance source...## 65. run of importance source...## 66. run of importance source...## 67. run of importance source...## 68. run of importance source...## 69. run of importance source...## 70. run of importance source...## 71. run of importance source...## 72. run of importance source...## 73. run of importance source...## 74. run of importance source...## 75. run of importance source...## 76. run of importance source...## 77. run of importance source...## 78. run of importance source...## 79. run of importance source...## 80. run of importance source...## 81. run of importance source...## 82. run of importance source...## 83. run of importance source...## 84. run of importance source...## 85. run of importance source...## 86. run of importance source...## 87. run of importance source...## 88. run of importance source...## 89. run of importance source...## 90. run of importance source...## 91. run of importance source...## 92. run of importance source...## 93. run of importance source...## 94. run of importance source...## 95. run of importance source...## 96. run of importance source...## 97. run of importance source...## 98. run of importance source...## 99. run of importance source...print(boruta_result)## Boruta performed 99 iterations in 8.100563 secs.
## 10 attributes confirmed important: V11, V12, V13, V2, V4 and 5 more;
## 1 attributes confirmed unimportant: V3;
## 1 tentative attributes left: V10;График
plot(boruta_result, las=2, cex.axis=0.7)
Вывод: определены значимые и незначимые признаки. ## R Markdown
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