From 8d0e384cc07e1dd769543ef29f056c663873e187 Mon Sep 17 00:00:00 2001 From: krzyzinskim Date: Tue, 24 Oct 2023 15:08:04 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20ModelOri?= =?UTF-8?q?ented/treeshap@62d11ea24f702bc77debaae0a0d32905a402bdc1=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- news/index.html | 2 +- pkgdown.yml | 2 +- reference/Rplot002.png | Bin 25726 -> 26983 bytes reference/gbm.unify-1.png | Bin 66940 -> 65679 bytes reference/predict.model_unified.html | 2 +- reference/ranger.unify-1.png | Bin 75325 -> 76862 bytes reference/ranger_surv.unify.html | 2 +- reference/set_reference_dataset.html | 472 +++++++++++++-------------- reference/unify-1.png | Bin 77415 -> 78677 bytes reference/unify-2.png | Bin 74121 -> 77717 bytes 10 files changed, 240 insertions(+), 240 deletions(-) diff --git a/news/index.html b/news/index.html index 196a96c..628b885 100644 --- a/news/index.html +++ b/news/index.html @@ -56,7 +56,7 @@

Changelog

- +
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kmSg(=xBLHz1j0g3X_@hB<{K+>&j}5JrInr`o|?S=U(qntD*ylh diff --git a/reference/ranger_surv.unify.html b/reference/ranger_surv.unify.html index 1cff263..1750461 100644 --- a/reference/ranger_surv.unify.html +++ b/reference/ranger_surv.unify.html @@ -103,7 +103,7 @@

Details

(Ishwaran et al. 2008). The final model prediction is made by averaging these CHFs from all the trees. To provide explanations in the form of a survival function, the CHFs from the leaves are converted into survival functions (SFs) using -the formula SF(t) = exp-CHF(t). +the formula SF(t) = exp(-CHF(t)). However, it is important to note that averaging these SFs does not yield the correct model prediction as the model prediction is the average of CHFs transformed in the same way. Therefore, when you obtain explanations based on the survival function, diff --git a/reference/set_reference_dataset.html b/reference/set_reference_dataset.html index b70fae1..ab46ce4 100644 --- a/reference/set_reference_dataset.html +++ b/reference/set_reference_dataset.html @@ -115,263 +115,263 @@

Examples

#> 1 0 0 overall <= 65.5 2 9 13 NA 501 #> 2 0 1 potential <= 73.5 3 4 8 NA 0 #> 3 0 2 <NA> <NA> NA NA NA NA -7000.000 0 -#> 4 0 3 overall <= 63.5 5 6 7 NA 0 -#> 5 0 4 <NA> <NA> NA NA NA NA 10000.000 0 -#> 6 0 5 <NA> <NA> NA NA NA NA 50000.000 0 -#> 7 0 6 <NA> <NA> NA NA NA NA 22704.082 0 -#> 8 0 7 <NA> <NA> NA NA NA NA -1455.238 0 +#> 4 0 3 overall <= 62.5 5 6 7 NA 0 +#> 5 0 4 <NA> <NA> NA NA NA NA 7500.000 0 +#> 6 0 5 <NA> <NA> NA NA NA NA 45000.000 0 +#> 7 0 6 <NA> <NA> NA NA NA NA 25603.448 0 +#> 8 0 7 <NA> <NA> NA NA NA NA -1137.133 0 #> 9 0 8 potential <= 68.5 10 11 12 NA 501 #> 10 0 9 <NA> <NA> NA NA NA NA 27500.000 0 -#> 11 0 10 <NA> <NA> NA NA NA NA 200000.000 501 -#> 12 0 11 <NA> <NA> NA NA NA NA 175935.918 0 -#> 13 0 12 <NA> <NA> NA NA NA NA 94412.463 0 +#> 11 0 10 <NA> <NA> NA NA NA NA 205000.000 501 +#> 12 0 11 <NA> <NA> NA NA NA NA 179448.039 0 +#> 13 0 12 <NA> <NA> NA NA NA NA 96595.032 0 #> 14 1 0 overall <= 66.5 15 22 26 NA 501 -#> 15 1 1 potential <= 73.5 16 17 21 NA 0 -#> 16 1 2 <NA> <NA> NA NA NA NA 1700.000 0 -#> 17 1 3 overall <= 62.5 18 19 20 NA 0 -#> 18 1 4 <NA> <NA> NA NA NA NA 10000.000 0 -#> 19 1 5 <NA> <NA> NA NA NA NA 45000.000 0 -#> 20 1 6 <NA> <NA> NA NA NA NA 29890.046 0 -#> 21 1 7 <NA> <NA> NA NA NA NA 6868.973 0 +#> 15 1 1 potential <= 71.5 16 17 21 NA 0 +#> 16 1 2 <NA> <NA> NA NA NA NA -1800.000 0 +#> 17 1 3 overall <= 63.5 18 19 20 NA 0 +#> 18 1 4 <NA> <NA> NA NA NA NA 11700.000 0 +#> 19 1 5 <NA> <NA> NA NA NA NA 43000.000 0 +#> 20 1 6 <NA> <NA> NA NA NA NA 24127.292 0 +#> 21 1 7 <NA> <NA> NA NA NA NA 5854.570 0 #> 22 1 8 potential <= 69.5 23 24 25 NA 501 -#> 23 1 9 <NA> <NA> NA NA NA NA 36000.000 0 -#> 24 1 10 <NA> <NA> NA NA NA NA 248500.000 501 -#> 25 1 11 <NA> <NA> NA NA NA NA 212883.330 0 -#> 26 1 12 <NA> <NA> NA NA NA NA 106663.869 0 +#> 23 1 9 <NA> <NA> NA NA NA NA 35500.000 0 +#> 24 1 10 <NA> <NA> NA NA NA NA 248000.000 501 +#> 25 1 11 <NA> <NA> NA NA NA NA 211341.790 0 +#> 26 1 12 <NA> <NA> NA NA NA NA 103348.014 0 #> 27 2 0 overall <= 67.5 28 35 39 NA 501 #> 28 2 1 overall <= 63.5 29 30 34 NA 0 -#> 29 2 2 <NA> <NA> NA NA NA NA -3470.000 0 -#> 30 2 3 age <= 24.5 31 32 33 NA 0 -#> 31 2 4 <NA> <NA> NA NA NA NA 40030.000 0 -#> 32 2 5 <NA> <NA> NA NA NA NA 21830.000 0 -#> 33 2 6 <NA> <NA> NA NA NA NA 29593.525 0 -#> 34 2 7 <NA> <NA> NA NA NA NA 10655.848 0 +#> 29 2 2 <NA> <NA> NA NA NA NA -3120.000 0 +#> 30 2 3 age <= 23.5 31 32 33 NA 0 +#> 31 2 4 <NA> <NA> NA NA NA NA 40700.000 0 +#> 32 2 5 <NA> <NA> NA NA NA NA 24430.000 0 +#> 33 2 6 <NA> <NA> NA NA NA NA 30140.566 0 +#> 34 2 7 <NA> <NA> NA NA NA NA 10843.546 0 #> 35 2 8 age <= 32.5 36 37 38 NA 501 -#> 36 2 9 <NA> <NA> NA NA NA NA 237150.000 435 -#> 37 2 10 <NA> <NA> NA NA NA NA 37150.000 66 -#> 38 2 11 <NA> <NA> NA NA NA NA 214202.632 0 -#> 39 2 12 <NA> <NA> NA NA NA NA 95290.685 0 +#> 36 2 9 <NA> <NA> NA NA NA NA 236700.000 435 +#> 37 2 10 <NA> <NA> NA NA NA NA 26700.000 66 +#> 38 2 11 <NA> <NA> NA NA NA NA 214614.927 0 +#> 39 2 12 <NA> <NA> NA NA NA NA 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