Convert large/infinite numeric values in a data.frame or task.
Source:R/capLargeValues.R
capLargeValues.RdConvert numeric entries which large/infinite (absolute) values in a data.frame or task. Only numeric/integer columns are affected.
capLargeValues( obj, target = character(0L), cols = NULL, threshold = Inf, impute = threshold, what = "abs" )
Arguments
| obj | (data.frame | Task) |
|---|---|
| target | (character) |
| cols | (character) |
| threshold | ( |
| impute | ( |
| what | ( |
Value
See also
Other eda_and_preprocess:
createDummyFeatures(),
dropFeatures(),
mergeSmallFactorLevels(),
normalizeFeatures(),
removeConstantFeatures(),
summarizeColumns(),
summarizeLevels()
Examples
capLargeValues(iris, threshold = 5, impute = 5)#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.0 3.5 1.4 0.2 setosa #> 2 4.9 3.0 1.4 0.2 setosa #> 3 4.7 3.2 1.3 0.2 setosa #> 4 4.6 3.1 1.5 0.2 setosa #> 5 5.0 3.6 1.4 0.2 setosa #> 6 5.0 3.9 1.7 0.4 setosa #> 7 4.6 3.4 1.4 0.3 setosa #> 8 5.0 3.4 1.5 0.2 setosa #> 9 4.4 2.9 1.4 0.2 setosa #> 10 4.9 3.1 1.5 0.1 setosa #> 11 5.0 3.7 1.5 0.2 setosa #> 12 4.8 3.4 1.6 0.2 setosa #> 13 4.8 3.0 1.4 0.1 setosa #> 14 4.3 3.0 1.1 0.1 setosa #> 15 5.0 4.0 1.2 0.2 setosa #> 16 5.0 4.4 1.5 0.4 setosa #> 17 5.0 3.9 1.3 0.4 setosa #> 18 5.0 3.5 1.4 0.3 setosa #> 19 5.0 3.8 1.7 0.3 setosa #> 20 5.0 3.8 1.5 0.3 setosa #> 21 5.0 3.4 1.7 0.2 setosa #> 22 5.0 3.7 1.5 0.4 setosa #> 23 4.6 3.6 1.0 0.2 setosa #> 24 5.0 3.3 1.7 0.5 setosa #> 25 4.8 3.4 1.9 0.2 setosa #> 26 5.0 3.0 1.6 0.2 setosa #> 27 5.0 3.4 1.6 0.4 setosa #> 28 5.0 3.5 1.5 0.2 setosa #> 29 5.0 3.4 1.4 0.2 setosa #> 30 4.7 3.2 1.6 0.2 setosa #> 31 4.8 3.1 1.6 0.2 setosa #> 32 5.0 3.4 1.5 0.4 setosa #> 33 5.0 4.1 1.5 0.1 setosa #> 34 5.0 4.2 1.4 0.2 setosa #> 35 4.9 3.1 1.5 0.2 setosa #> 36 5.0 3.2 1.2 0.2 setosa #> 37 5.0 3.5 1.3 0.2 setosa #> 38 4.9 3.6 1.4 0.1 setosa #> 39 4.4 3.0 1.3 0.2 setosa #> 40 5.0 3.4 1.5 0.2 setosa #> 41 5.0 3.5 1.3 0.3 setosa #> 42 4.5 2.3 1.3 0.3 setosa #> 43 4.4 3.2 1.3 0.2 setosa #> 44 5.0 3.5 1.6 0.6 setosa #> 45 5.0 3.8 1.9 0.4 setosa #> 46 4.8 3.0 1.4 0.3 setosa #> 47 5.0 3.8 1.6 0.2 setosa #> 48 4.6 3.2 1.4 0.2 setosa #> 49 5.0 3.7 1.5 0.2 setosa #> 50 5.0 3.3 1.4 0.2 setosa #> 51 5.0 3.2 4.7 1.4 versicolor #> 52 5.0 3.2 4.5 1.5 versicolor #> 53 5.0 3.1 4.9 1.5 versicolor #> 54 5.0 2.3 4.0 1.3 versicolor #> 55 5.0 2.8 4.6 1.5 versicolor #> 56 5.0 2.8 4.5 1.3 versicolor #> 57 5.0 3.3 4.7 1.6 versicolor #> 58 4.9 2.4 3.3 1.0 versicolor #> 59 5.0 2.9 4.6 1.3 versicolor #> 60 5.0 2.7 3.9 1.4 versicolor #> 61 5.0 2.0 3.5 1.0 versicolor #> 62 5.0 3.0 4.2 1.5 versicolor #> 63 5.0 2.2 4.0 1.0 versicolor #> 64 5.0 2.9 4.7 1.4 versicolor #> 65 5.0 2.9 3.6 1.3 versicolor #> 66 5.0 3.1 4.4 1.4 versicolor #> 67 5.0 3.0 4.5 1.5 versicolor #> 68 5.0 2.7 4.1 1.0 versicolor #> 69 5.0 2.2 4.5 1.5 versicolor #> 70 5.0 2.5 3.9 1.1 versicolor #> 71 5.0 3.2 4.8 1.8 versicolor #> 72 5.0 2.8 4.0 1.3 versicolor #> 73 5.0 2.5 4.9 1.5 versicolor #> 74 5.0 2.8 4.7 1.2 versicolor #> 75 5.0 2.9 4.3 1.3 versicolor #> 76 5.0 3.0 4.4 1.4 versicolor #> 77 5.0 2.8 4.8 1.4 versicolor #> 78 5.0 3.0 5.0 1.7 versicolor #> 79 5.0 2.9 4.5 1.5 versicolor #> 80 5.0 2.6 3.5 1.0 versicolor #> 81 5.0 2.4 3.8 1.1 versicolor #> 82 5.0 2.4 3.7 1.0 versicolor #> 83 5.0 2.7 3.9 1.2 versicolor #> 84 5.0 2.7 5.0 1.6 versicolor #> 85 5.0 3.0 4.5 1.5 versicolor #> 86 5.0 3.4 4.5 1.6 versicolor #> 87 5.0 3.1 4.7 1.5 versicolor #> 88 5.0 2.3 4.4 1.3 versicolor #> 89 5.0 3.0 4.1 1.3 versicolor #> 90 5.0 2.5 4.0 1.3 versicolor #> 91 5.0 2.6 4.4 1.2 versicolor #> 92 5.0 3.0 4.6 1.4 versicolor #> 93 5.0 2.6 4.0 1.2 versicolor #> 94 5.0 2.3 3.3 1.0 versicolor #> 95 5.0 2.7 4.2 1.3 versicolor #> 96 5.0 3.0 4.2 1.2 versicolor #> 97 5.0 2.9 4.2 1.3 versicolor #> 98 5.0 2.9 4.3 1.3 versicolor #> 99 5.0 2.5 3.0 1.1 versicolor #> 100 5.0 2.8 4.1 1.3 versicolor #> 101 5.0 3.3 5.0 2.5 virginica #> 102 5.0 2.7 5.0 1.9 virginica #> 103 5.0 3.0 5.0 2.1 virginica #> 104 5.0 2.9 5.0 1.8 virginica #> 105 5.0 3.0 5.0 2.2 virginica #> 106 5.0 3.0 5.0 2.1 virginica #> 107 4.9 2.5 4.5 1.7 virginica #> 108 5.0 2.9 5.0 1.8 virginica #> 109 5.0 2.5 5.0 1.8 virginica #> 110 5.0 3.6 5.0 2.5 virginica #> 111 5.0 3.2 5.0 2.0 virginica #> 112 5.0 2.7 5.0 1.9 virginica #> 113 5.0 3.0 5.0 2.1 virginica #> 114 5.0 2.5 5.0 2.0 virginica #> 115 5.0 2.8 5.0 2.4 virginica #> 116 5.0 3.2 5.0 2.3 virginica #> 117 5.0 3.0 5.0 1.8 virginica #> 118 5.0 3.8 5.0 2.2 virginica #> 119 5.0 2.6 5.0 2.3 virginica #> 120 5.0 2.2 5.0 1.5 virginica #> 121 5.0 3.2 5.0 2.3 virginica #> 122 5.0 2.8 4.9 2.0 virginica #> 123 5.0 2.8 5.0 2.0 virginica #> 124 5.0 2.7 4.9 1.8 virginica #> 125 5.0 3.3 5.0 2.1 virginica #> 126 5.0 3.2 5.0 1.8 virginica #> 127 5.0 2.8 4.8 1.8 virginica #> 128 5.0 3.0 4.9 1.8 virginica #> 129 5.0 2.8 5.0 2.1 virginica #> 130 5.0 3.0 5.0 1.6 virginica #> 131 5.0 2.8 5.0 1.9 virginica #> 132 5.0 3.8 5.0 2.0 virginica #> 133 5.0 2.8 5.0 2.2 virginica #> 134 5.0 2.8 5.0 1.5 virginica #> 135 5.0 2.6 5.0 1.4 virginica #> 136 5.0 3.0 5.0 2.3 virginica #> 137 5.0 3.4 5.0 2.4 virginica #> 138 5.0 3.1 5.0 1.8 virginica #> 139 5.0 3.0 4.8 1.8 virginica #> 140 5.0 3.1 5.0 2.1 virginica #> 141 5.0 3.1 5.0 2.4 virginica #> 142 5.0 3.1 5.0 2.3 virginica #> 143 5.0 2.7 5.0 1.9 virginica #> 144 5.0 3.2 5.0 2.3 virginica #> 145 5.0 3.3 5.0 2.5 virginica #> 146 5.0 3.0 5.0 2.3 virginica #> 147 5.0 2.5 5.0 1.9 virginica #> 148 5.0 3.0 5.0 2.0 virginica #> 149 5.0 3.4 5.0 2.3 virginica #> 150 5.0 3.0 5.0 1.8 virginica