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[WIP] Feature/more tests #66

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[WIP] Feature/more tests #66

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kkondo1981
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See #65 .

@kkondo1981 kkondo1981 added the WIP Work In Progress label Jun 12, 2021
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  • Added vehicle insurance dataset with Gamma(link=log) AGLM
  • Fixed residuals() to handle general case. Note that old implementation other than deviance residuals seems easy to integrated into the new implementation, but remain it for a while because I need some regression test before changing it.

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  • Added a demo for French mortor TPL dataset with Poisson(link=log) AGLM.
  • Simplified residuals() as written in the previous comment, because I checked new implementation doesn't change results with Poisson case.

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  • Added a demo for MultinomialExample in glmnet with family="multinomial".
  • Modified plot.AccurateGLM() and coef.AccurateGLM() so that they can be used with multinomial regression. Note that residual.AccurateGLM() is not modified and couldn't handle with multinomial cases properly.
  • Added "demo/README.md" to show results of demos.

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  • Added a demo for the banknotes dataset with family="binomial".
  • Update all other demos and demo/README.md to compare AGLM with simple GLM (with cross-validation for alpha and lambda).
  • Modified aglm() and cv.aglm() to cope with binomial and multinomial regressions. Also modified residuals.AccurateGLM() to cope with binomial regressions (actually there was a bug and I fixed it) , but not finished for multinomial regressions.

… plot in multinomial cases.

- Added `use_legend` and `margin` for `plot.AccurateGLM()` for adjusting (mainly) improving plotting for multinomial cases.
- apply margins for barplot case too,
- use legends in multinomial cases for barplot,
- add the `color` parameter which works in all the cases of `lines`, `barplot`, `boxplot`.
…` for changing colors of graphic components.
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kkondo1981 commented Jul 11, 2021

Modified plot.AccurateGLM(), mainly to adjust visuals in the case of multinomial regression.
Now plot.AccurateGLM():

  • draws components curves (or bars) of multiple classes in one plot instead of multiple plots,
  • has the parameter to use legends to distinguish components curves (or bars) of multiple classes (use_legend),
  • and has the parameters to adjusting colors of graphic components (col, resid_col, smooth_col, rug_col).

Furthermore, I disallowed to use resid=TRUE in multinomial cases, because plotting those may result slightly too complicated graphs.

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