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A classification task for the popular datasets::iris data set. Just like the iris task, but the features are represented as one lazy tensor column.

Format

R6::R6Class inheriting from mlr3::TaskClassif.

Construction

tsk("lazy_iris")

Properties

  • Task type: “classif”

  • Properties: “multiclass”

  • Has Missings: no

  • Target: “Species”

  • Features: “x”

  • Data Dimension: 150x3

References

Anderson E (1936). “The Species Problem in Iris.” Annals of the Missouri Botanical Garden, 23(3), 457. doi:10.2307/2394164 .

Examples

task = tsk("lazy_iris")
task
#> 
#> ── <TaskClassif> (150x2): Iris Flowers ─────────────────────────────────────────
#> • Target: Species
#> • Target classes: setosa (33%), versicolor (33%), virginica (33%)
#> • Properties: multiclass
#> • Features (1):
#>   • lt (1): x
df = task$data()
materialize(df$x[1:6], rbind = TRUE)
#> torch_tensor
#>  5.1000  3.5000  1.4000  0.2000
#>  4.9000  3.0000  1.4000  0.2000
#>  4.7000  3.2000  1.3000  0.2000
#>  4.6000  3.1000  1.5000  0.2000
#>  5.0000  3.6000  1.4000  0.2000
#>  5.4000  3.9000  1.7000  0.4000
#> [ CPUFloatType{6,4} ]