Internal Function for Split Points for Selected Variables
This function calculate candidate splits for each selected variable. For numerical variables splits are calculated as percentiles (in general uniform quantiles of the length grid_points). For all other variables splits are calculated as unique values.
calculate_variable_split(data, variables = colnames(data), grid_points = 101)
Arguments
| data | validation dataset. Is used to determine distribution of observations. |
|---|---|
| variables | names of variables for which splits shall be calculated |
| grid_points | number of points used for response path |
Value
A named list with splits for selected variables
Details
Note that calculate_variable_split function is S3 generic.
If you want to work on non standard data sources (like H2O ddf, external databases)
you should overload it.
Examples
library("DALEX2")library("randomForest") set.seed(59) apartments_rf_model <- randomForest(m2.price ~ construction.year + surface + floor + no.rooms + district, data = apartments) vars <- c("construction.year", "surface", "floor", "no.rooms", "district") calculate_variable_split(apartments, vars)#> $construction.year #> 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% #> 1920.00 1921.00 1922.00 1923.00 1924.00 1925.00 1926.00 1927.00 1927.00 1928.00 #> 10% 11% 12% 13% 14% 15% 16% 17% 18% 19% #> 1929.00 1929.89 1931.00 1932.00 1933.00 1934.00 1934.84 1935.00 1936.00 1937.00 #> 20% 21% 22% 23% 24% 25% 26% 27% 28% 29% #> 1938.00 1939.00 1940.00 1941.00 1941.76 1943.00 1944.00 1945.00 1946.00 1946.00 #> 30% 31% 32% 33% 34% 35% 36% 37% 38% 39% #> 1947.00 1948.00 1949.00 1949.00 1950.00 1951.00 1952.00 1953.00 1954.00 1956.00 #> 40% 41% 42% 43% 44% 45% 46% 47% 48% 49% #> 1956.00 1957.00 1957.00 1958.00 1959.00 1959.00 1960.00 1961.53 1962.52 1963.51 #> 50% 51% 52% 53% 54% 55% 56% 57% 58% 59% #> 1965.00 1965.00 1967.00 1967.47 1968.00 1969.00 1970.00 1971.00 1971.00 1972.00 #> 60% 61% 62% 63% 64% 65% 66% 67% 68% 69% #> 1973.00 1974.39 1975.00 1977.00 1977.00 1978.00 1980.00 1981.00 1982.00 1983.00 #> 70% 71% 72% 73% 74% 75% 76% 77% 78% 79% #> 1984.00 1985.00 1985.00 1986.00 1987.00 1988.00 1989.00 1990.00 1990.00 1991.00 #> 80% 81% 82% 83% 84% 85% 86% 87% 88% 89% #> 1992.00 1993.00 1993.18 1994.00 1995.00 1996.00 1997.00 1997.00 1998.00 1999.00 #> 90% 91% 92% 93% 94% 95% 96% 97% 98% 99% #> 2000.00 2001.00 2002.00 2003.00 2004.00 2005.00 2005.00 2007.00 2008.00 2009.00 #> 100% #> 2010.00 #> #> $surface #> 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% #> 20.00 22.00 23.98 24.00 25.00 26.00 27.00 30.00 31.00 32.00 33.00 #> 11% 12% 13% 14% 15% 16% 17% 18% 19% 20% 21% #> 35.00 37.00 38.00 39.00 40.00 41.00 42.00 44.00 46.00 47.00 48.00 #> 22% 23% 24% 25% 26% 27% 28% 29% 30% 31% 32% #> 49.78 51.00 52.00 53.00 54.00 55.73 56.72 57.00 59.00 60.00 61.00 #> 33% 34% 35% 36% 37% 38% 39% 40% 41% 42% 43% #> 62.00 63.00 64.00 65.64 67.00 68.62 70.00 72.00 73.59 75.00 76.00 #> 44% 45% 46% 47% 48% 49% 50% 51% 52% 53% 54% #> 78.00 79.55 81.00 82.00 83.00 84.00 85.50 87.00 88.48 90.00 91.00 #> 55% 56% 57% 58% 59% 60% 61% 62% 63% 64% 65% #> 93.00 93.44 95.00 96.00 98.00 100.00 101.39 103.00 105.00 105.00 106.00 #> 66% 67% 68% 69% 70% 71% 72% 73% 74% 75% 76% #> 107.00 108.00 109.00 110.00 111.00 112.00 113.00 114.27 116.00 118.00 120.00 #> 77% 78% 79% 80% 81% 82% 83% 84% 85% 86% 87% #> 121.00 123.00 124.00 125.00 127.00 127.00 128.00 130.00 131.00 132.00 133.00 #> 88% 89% 90% 91% 92% 93% 94% 95% 96% 97% 98% #> 136.00 137.00 138.00 141.00 142.00 143.00 144.00 145.00 146.04 147.03 148.00 #> 99% 100% #> 149.00 150.00 #> #> $floor #> 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% #> 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.91 2.00 2.00 2.00 #> 13% 14% 15% 16% 17% 18% 19% 20% 21% 22% 23% 24% 25% #> 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 3.00 3.00 3.00 3.00 3.00 #> 26% 27% 28% 29% 30% 31% 32% 33% 34% 35% 36% 37% 38% #> 3.00 3.00 3.00 3.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 5.00 #> 39% 40% 41% 42% 43% 44% 45% 46% 47% 48% 49% 50% 51% #> 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 6.00 6.00 6.00 6.00 #> 52% 53% 54% 55% 56% 57% 58% 59% 60% 61% 62% 63% 64% #> 6.00 6.00 6.00 6.00 6.00 6.00 7.00 7.00 7.00 7.00 7.00 7.00 7.00 #> 65% 66% 67% 68% 69% 70% 71% 72% 73% 74% 75% 76% 77% #> 7.00 7.00 7.00 7.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 #> 78% 79% 80% 81% 82% 83% 84% 85% 86% 87% 88% 89% 90% #> 8.00 9.00 9.00 9.00 9.00 9.00 9.00 9.00 9.00 9.00 9.00 9.00 10.00 #> 91% 92% 93% 94% 95% 96% 97% 98% 99% 100% #> 10.00 10.00 10.00 10.00 10.00 10.00 10.00 10.00 10.00 10.00 #> #> $no.rooms #> 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15% #> 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 #> 16% 17% 18% 19% 20% 21% 22% 23% 24% 25% 26% 27% 28% 29% 30% 31% #> 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 #> 32% 33% 34% 35% 36% 37% 38% 39% 40% 41% 42% 43% 44% 45% 46% 47% #> 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 #> 48% 49% 50% 51% 52% 53% 54% 55% 56% 57% 58% 59% 60% 61% 62% 63% #> 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 #> 64% 65% 66% 67% 68% 69% 70% 71% 72% 73% 74% 75% 76% 77% 78% 79% #> 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 #> 80% 81% 82% 83% 84% 85% 86% 87% 88% 89% 90% 91% 92% 93% 94% 95% #> 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 #> 96% 97% 98% 99% 100% #> 6 6 6 6 6 #> #> $district #> [1] Srodmiescie Bielany Praga Ochota Mokotow Ursus #> [7] Zoliborz Wola Bemowo Ursynow #> 10 Levels: Bemowo Bielany Mokotow Ochota Praga Srodmiescie Ursus ... Zoliborz #>