Description Usage Arguments Value References Examples

View source: R/predict_diagnostics.R

This function performs local diagnostic of residuals. For a single instance its neighbors are identified in the validation data. Residuals are calculated for neighbors and plotted against residuals for all data. Find information how to use this function here: https://pbiecek.github.io/ema/localDiagnostics.html.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
predict_diagnostics(
explainer,
new_observation,
variables = NULL,
...,
nbins = 20,
neighbors = 50,
distance = gower::gower_dist
)
individual_diagnostics(
explainer,
new_observation,
variables = NULL,
...,
nbins = 20,
neighbors = 50,
distance = gower::gower_dist
)
``` |

`explainer` |
a model to be explained, preprocessed by the 'explain' function |

`new_observation` |
a new observation for which predictions need to be explained |

`variables` |
character - name of variables to be explained |

`...` |
other parameters |

`nbins` |
number of bins for the histogram. By default 20 |

`neighbors` |
number of neighbors for histogram. By default 50. |

`distance` |
the distance function, by default the |

An object of the class 'predict_diagnostics'. It's a data frame with calculated distribution of residuals.

Explanatory Model Analysis. Explore, Explain and Examine Predictive Models. https://pbiecek.github.io/ema/

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
library("ranger")
titanic_glm_model <- ranger(survived ~ gender + age + class + fare + sibsp + parch,
data = titanic_imputed)
explainer_glm <- explain(titanic_glm_model,
data = titanic_imputed,
y = titanic_imputed$survived)
johny_d <- titanic_imputed[24, c("gender", "age", "class", "fare", "sibsp", "parch")]
## Not run:
id_johny <- predict_diagnostics(explainer_glm, johny_d, variables = NULL)
id_johny
plot(id_johny)
id_johny <- predict_diagnostics(explainer_glm, johny_d,
neighbors = 10,
variables = c("age", "fare"))
id_johny
plot(id_johny)
id_johny <- predict_diagnostics(explainer_glm,
johny_d,
neighbors = 10,
variables = c("class", "gender"))
id_johny
plot(id_johny)
## End(Not run)
``` |

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