Predict visual signal strength for bootstrapped residual plots
Source:R/zzz_auto_visual_inference.R
AUTO_VI-cash-boot_vss.Rd
This function bootstrap the data and refits the model, then predicts the visual signal strength of the bootstrapped residual plots.
Arguments
- draws
Integer. Number of simulation draws.
- fitted_model
Model. A model object, e.g.
lm
.- keras_model
Keras model. A trained computer vision model.
- data
Data frame. The data used to fit the model. See also
AUTO_VI$get_data()
.- node_index
Integer. An index indicating which node of the output layer contains the visual signal strength. This is particularly useful when the keras model has more than one output nodes.
- keep_boot_data
Boolean. Whether to keep the bootstrapped data.
- keep_boot_plot
Boolean. Whether to keep the bootstrapped plots.
- extract_feature_from_layer
Character/Integer. A layer name or an integer layer index for extracting features from a layer.
Examples
keras_model <- try(get_keras_model("vss_phn_32"))
if (!inherits(keras_model, "try-error")) {
myvi <- auto_vi(lm(dist ~ speed, data = cars), keras_model)
myvi$boot_vss()
}
#> ✔ Generate bootstrapped data.
#> ✔ Generate bootstrapped plots.
#> Warning: Problem in area computation (Returns NA)
#> Computing auxiliary inputs ■■■■■■■■■■ 29% | ETA: 2s
#> Warning: shull: complete hull invisible, data scaling error, will retry with some jitter
#> Warning: shull: complete hull invisible, data scaling error, will retry with some jitter
#> Warning: shull: complete hull invisible, data scaling error, will retry with some jitter
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: shull: complete hull invisible, data scaling error, will retry with some jitter
#> Warning: Problem in area computation (Returns NA)
#> Warning: shull: complete hull invisible, data scaling error, will retry with some jitter
#> Warning: no non-missing arguments to min; returning Inf
#> Computing auxiliary inputs ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■ 100% | ETA: 0s
#> ✔ Compute auxilary inputs.
#> Saving images ■■■■■■■■■■ 29% | ETA: 2s
#> Saving images ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■ 98% | ETA: 0s
#> Saving images ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■ 100% | ETA: 0s
#> ✔ Predict visual signal strength for 100 images.
#> # A tibble: 100 × 1
#> vss
#> <dbl>
#> 1 2.86
#> 2 0.876
#> 3 2.29
#> 4 3.20
#> 5 3.11
#> 6 2.73
#> 7 3.53
#> 8 3.24
#> 9 2.58
#> 10 2.93
#> # ℹ 90 more rows