Skip to content

Commit

Permalink
rebuild docs
Browse files Browse the repository at this point in the history
  • Loading branch information
@JohnMount
JohnMount committed Dec 8, 2019
1 parent 5750cef commit b8d6e20
Show file tree
Hide file tree
Showing 56 changed files with 467 additions and 433 deletions.
2 changes: 1 addition & 1 deletion DESCRIPTION
View file
Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@ Package: vtreat
Type: Package
Title: A Statistically Sound 'data.frame' Processor/Conditioner
Version: 1.4.8
Date: 2019-12-07
Date: 2019-12-08
Authors@R: c(
person("John", "Mount", email = "[email protected]", role = c("aut", "cre")),
person("Nina", "Zumel", email = "[email protected]", role = c("aut")),
Expand Down
2 changes: 1 addition & 1 deletion Examples/Classification/Classification_FT.Rmd
View file
Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@ output: github_document
Nina Zumel and John Mount
December 2019

Note this the "fit_transform" variation (a notation closer to that used in [`pyvtreat`](https://github.com/WinVector/pyvtreat)) of the description of the [`R` version of `vtreat`](https://github.com/WinVector/vtreat). The original `vtreat` notation version can be found [here](https://github.com/WinVector/vtreat/blob/master/Examples/Classification/Classification.md). The same example for the [`Python` version of `vtreat`](https://github.com/WinVector/pyvtreat) can be found [here](https://github.com/WinVector/pyvtreat/blob/master/Examples/Classification/Classification.md).
This is the ["fit_transform" variation](https://github.com/WinVector/vtreat/blob/master/Examples/fit_transform/fit_transform_api.md) (a notation closer to that used in [`pyvtreat`](https://github.com/WinVector/pyvtreat)) of the description of the [`R` version of `vtreat`](https://github.com/WinVector/vtreat). The original `vtreat` notation version can be found [here](https://github.com/WinVector/vtreat/blob/master/Examples/Classification/Classification.md). The same example for the [`Python` version of `vtreat`](https://github.com/WinVector/pyvtreat) can be found [here](https://github.com/WinVector/pyvtreat/blob/master/Examples/Classification/Classification.md).

## Preliminaries

Expand Down
83 changes: 42 additions & 41 deletions Examples/Classification/Classification_FT.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -5,11 +5,12 @@ Classification Fit Transform Notation

Nina Zumel and John Mount December 2019

Note this the “fit\_transform” variation (a notation closer to that used
in [`pyvtreat`](https://github.com/WinVector/pyvtreat)) of the
description of the [`R` version of
`vtreat`](https://github.com/WinVector/vtreat). The original `vtreat`
notation version can be found
This is the [“fit\_transform”
variation](https://github.com/WinVector/vtreat/blob/master/Examples/fit_transform/fit_transform_api.md)
(a notation closer to that used in
[`pyvtreat`](https://github.com/WinVector/pyvtreat)) of the description
of the [`R` version of `vtreat`](https://github.com/WinVector/vtreat).
The original `vtreat` notation version can be found
[here](https://github.com/WinVector/vtreat/blob/master/Examples/Classification/Classification.md).
The same example for the [`Python` version of
`vtreat`](https://github.com/WinVector/pyvtreat) can be found
Expand Down Expand Up @@ -61,14 +62,14 @@ d %.>%
knitr::kable(.)
```

| x | y | xc | x2 | yc |
| ---------: | ----------: | :---------- | ----------: | :---- |
| 6.302692 | \-0.1295796 | level\_0 | 0.4567776 | FALSE |
| \-1.492638 | \-1.0181135 | NA | 0.6904050 | FALSE |
| 9.011422 | 0.2406594 | level\_0 | 2.1542995 | FALSE |
| NA | \-0.5377555 | level\_-0.5 | \-0.1497430 | FALSE |
| NA | 0.9582693 | level\_1 | \-0.9892123 | TRUE |
| NA | \-1.0622297 | NA | 0.0241504 | FALSE |
| x | y | xc | x2 | yc |
| ---------: | ----------: | :--------- | ----------: | :---- |
| \-1.467457 | \-0.8627028 | NA | \-0.5020452 | FALSE |
| 2.458423 | 0.4957986 | level\_0.5 | \-1.1586586 | FALSE |
| 1.043813 | 0.8511840 | level\_1 | \-0.7916552 | TRUE |
| NA | \-0.0537814 | level\_0 | \-1.7720515 | FALSE |
| NA | 0.3547501 | level\_0.5 | 0.3095969 | FALSE |
| NA | 0.7160672 | level\_0.5 | 1.7166199 | TRUE |

### Some quick data exploration

Expand All @@ -79,27 +80,27 @@ unique(d['xc'])
```

## xc
## 1 level_0
## 2 <NA>
## 4 level_-0.5
## 5 level_1
## 8 level_0.5
## 1 <NA>
## 2 level_0.5
## 3 level_1
## 4 level_0
## 7 level_-0.5

``` r
table(d$xc, useNA = 'always')
```

##
## level_-0.5 level_0 level_0.5 level_1 <NA>
## 95 71 114 114 106
## 95 70 101 123 111

Find the mean value of `yc`

``` r
mean(d[['yc']])
```

## [1] 0.352
## [1] 0.35

Plot of `yc` versus `x`.

Expand Down Expand Up @@ -157,16 +158,16 @@ knitr::kable(score_frame)

| varName | varMoves | rsq | sig | needsSplit | extraModelDegrees | origName | code | recommended |
| :----------------------------- | :------- | --------: | --------: | :--------- | ----------------: | :------- | :---- | :---------- |
| x | TRUE | 0.0013210 | 0.3546032 | FALSE | 0 | x | clean | FALSE |
| x\_isBAD | TRUE | 0.0002178 | 0.7070100 | FALSE | 0 | x | isBAD | FALSE |
| xc\_catP | TRUE | 0.3915048 | 0.0000000 | TRUE | 4 | xc | catP | TRUE |
| xc\_catB | TRUE | 0.7542349 | 0.0000000 | TRUE | 4 | xc | catB | TRUE |
| x2 | TRUE | 0.0000596 | 0.8440993 | FALSE | 0 | x2 | clean | FALSE |
| xc\_lev\_NA | TRUE | 0.1648922 | 0.0000000 | FALSE | 0 | xc | lev | TRUE |
| xc\_lev\_x\_level\_minus\_0\_5 | TRUE | 0.1451918 | 0.0000000 | FALSE | 0 | xc | lev | TRUE |
| xc\_lev\_x\_level\_0 | TRUE | 0.1045998 | 0.0000000 | FALSE | 0 | xc | lev | TRUE |
| xc\_lev\_x\_level\_0\_5 | TRUE | 0.0354874 | 0.0000016 | FALSE | 0 | xc | lev | TRUE |
| xc\_lev\_x\_level\_1 | TRUE | 0.4755162 | 0.0000000 | FALSE | 0 | xc | lev | TRUE |
| x | TRUE | 0.0026693 | 0.1886367 | FALSE | 0 | x | clean | FALSE |
| x\_isBAD | TRUE | 0.0002891 | 0.6652732 | FALSE | 0 | x | isBAD | FALSE |
| xc\_catP | TRUE | 0.3536967 | 0.0000000 | TRUE | 4 | xc | catP | TRUE |
| xc\_catB | TRUE | 0.7827645 | 0.0000000 | TRUE | 4 | xc | catB | TRUE |
| x2 | TRUE | 0.0005606 | 0.5468663 | FALSE | 0 | x2 | clean | FALSE |
| xc\_lev\_NA | TRUE | 0.1731335 | 0.0000000 | FALSE | 0 | xc | lev | TRUE |
| xc\_lev\_x\_level\_minus\_0\_5 | TRUE | 0.1443975 | 0.0000000 | FALSE | 0 | xc | lev | TRUE |
| xc\_lev\_x\_level\_0 | TRUE | 0.1024190 | 0.0000000 | FALSE | 0 | xc | lev | TRUE |
| xc\_lev\_x\_level\_0\_5 | TRUE | 0.0225307 | 0.0001338 | FALSE | 0 | xc | lev | TRUE |
| xc\_lev\_x\_level\_1 | TRUE | 0.5327844 | 0.0000000 | FALSE | 0 | xc | lev | TRUE |

Note that the variable `xc` has been converted to multiple variables:

Expand Down Expand Up @@ -231,14 +232,14 @@ d_prepared %.>%
knitr::kable(.)
```

| x | x\_isBAD | xc\_catP | xc\_catB | x2 | xc\_lev\_NA | xc\_lev\_x\_level\_minus\_0\_5 | xc\_lev\_x\_level\_0 | xc\_lev\_x\_level\_0\_5 | xc\_lev\_x\_level\_1 | yc |
| ----------: | -------: | --------: | ---------: | ----------: | ----------: | -----------------------------: | -------------------: | ----------------------: | -------------------: | :---- |
| 6.3026920 | 0 | 0.1381381 | \-12.42588 | 0.4567776 | 0 | 0 | 1 | 0 | 0 | FALSE |
| \-1.4926379 | 0 | 0.2102102 | \-12.84573 | 0.6904050 | 1 | 0 | 0 | 0 | 0 | FALSE |
| 9.0114217 | 0 | 0.1381381 | \-12.42588 | 2.1542995 | 0 | 0 | 1 | 0 | 0 | FALSE |
| \-0.1894789 | 1 | 0.1976048 | \-12.79540 | \-0.1497430 | 0 | 1 | 0 | 0 | 0 | FALSE |
| 0.3048341 | 1 | 0.2282282 | 14.15418 | \-0.9892123 | 0 | 0 | 0 | 0 | 1 | TRUE |
| 0.3048341 | 1 | 0.2102102 | \-12.84573 | 0.0241504 | 1 | 0 | 0 | 0 | 0 | FALSE |
| x | x\_isBAD | xc\_catP | xc\_catB | x2 | xc\_lev\_NA | xc\_lev\_x\_level\_minus\_0\_5 | xc\_lev\_x\_level\_0 | xc\_lev\_x\_level\_0\_5 | xc\_lev\_x\_level\_1 | yc |
| ----------: | -------: | --------: | -----------: | ----------: | ----------: | -----------------------------: | -------------------: | ----------------------: | -------------------: | :---- |
| \-1.4674566 | 0 | 0.2252252 | \-12.9015231 | \-0.5020452 | 1 | 0 | 0 | 0 | 0 | FALSE |
| 2.4584227 | 0 | 0.1831832 | 0.6458938 | \-1.1586586 | 0 | 0 | 0 | 1 | 0 | FALSE |
| 1.0438128 | 0 | 0.2335329 | 14.1847735 | \-0.7916552 | 0 | 0 | 0 | 0 | 1 | TRUE |
| 0.0248760 | 1 | 0.1321321 | \-12.3814282 | \-1.7720515 | 0 | 0 | 1 | 0 | 0 | FALSE |
| 0.1336182 | 1 | 0.2185629 | 0.7549238 | 0.3095969 | 0 | 0 | 0 | 1 | 0 | FALSE |
| 0.1336182 | 1 | 0.2185629 | 0.7549238 | 1.7166199 | 0 | 0 | 0 | 1 | 0 | TRUE |

## A Closer Look at `catB` variables

Expand Down Expand Up @@ -501,9 +502,9 @@ d %.>%

| rsq | count | sig | var |
| ----------: | ----: | --------: | :-- |
| 0.001321023 | 2 | 0.7092064 | x |
| 0.001335232 | 3 | 1.0000000 | x2 |
| 0.755567579 | 2 | 0.0000000 | xc |
| 0.002669305 | 2 | 0.3772735 | x |
| 0.001029486 | 3 | 1.0000000 | x2 |
| 0.782546773 | 2 | 0.0000000 | xc |

More on non-linear variable scoring can be found
[here](https://cran.r-project.org/web/packages/vtreat/vignettes/VariableImportance.html).
Expand Down
Binary file modified Examples/Classification/Classification_FT_files/figure-gfm/unnamed-chunk-12-1.png
View file
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file modified Examples/Classification/Classification_FT_files/figure-gfm/unnamed-chunk-13-1.png
View file
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file modified Examples/Classification/Classification_FT_files/figure-gfm/unnamed-chunk-14-1.png
View file
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file modified Examples/Classification/Classification_FT_files/figure-gfm/unnamed-chunk-15-1.png
View file
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file modified Examples/Classification/Classification_FT_files/figure-gfm/unnamed-chunk-6-1.png
View file
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
2 changes: 1 addition & 1 deletion Examples/Multinomial/MultinomialExample_FT.Rmd
View file
Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@ output: github_document
Nina Zumel and John Mount
October 2019

Note this the "fit_transform" variation (a notation closer to that used in [`pyvtreat`](https://github.com/WinVector/pyvtreat)) of the description of the [`R` version of `vtreat`](https://github.com/WinVector/vtreat). The original `vtreat` notation version can be found [here](https://github.com/WinVector/vtreat/blob/master/Examples/Multinomial/MultinomialExample.md). The same example for the [`Python` version of `vtreat`](https://github.com/WinVector/pyvtreat) can be found [here](https://github.com/WinVector/pyvtreat/blob/master/Examples/Multinomial/MultinomialExample.md).
This is the ["fit_transform" variation](https://github.com/WinVector/vtreat/blob/master/Examples/fit_transform/fit_transform_api.md) (a notation closer to that used in [`pyvtreat`](https://github.com/WinVector/pyvtreat)) of the description of the [`R` version of `vtreat`](https://github.com/WinVector/vtreat). The original `vtreat` notation version can be found [here](https://github.com/WinVector/vtreat/blob/master/Examples/Multinomial/MultinomialExample.md). The same example for the [`Python` version of `vtreat`](https://github.com/WinVector/pyvtreat) can be found [here](https://github.com/WinVector/pyvtreat/blob/master/Examples/Multinomial/MultinomialExample.md).

## Preliminaries

Expand Down
Loading

0 comments on commit b8d6e20

Please sign in to comment.