add OutlierScore, Continuous <: IID

tweak

Author: ablaom

docs/src/index.md

@@ -105,14 +105,15 @@ by the clustering algorithm can can be paired with human labels using, say, the
 index. In survival analysis, predicted survival functions or probability distributions are
 compared with censored ground truth survival times.
 
-More generally, whenever we have predicted variable (e.g., a class label) paired with
+More generally, whenever we have a predicted variable (e.g., a class label) paired with
 itself or some proxy (such as a class probability) we call the variable a *target*
 variable, and the predicted output a *target proxy*. It is immaterial whether or not the
 target appears in training (is supervised) or whether the model generalizes to new
-observations (learns) or not. The target and the kind of predicted proxy are crucial
-features of ML/statistics performance measures and LearnAPI.jl provides a detailed list of
-proxy dispatch types (see [Target proxies](@ref)), as well as algorithm traits to
-articulate target type /scitype and a preferred kind of target proxy.
+observations (learns) or not. 
+
+The target and the kind of predicted proxy are crucial features of ML/statistics
+performance measures and LearnAPI.jl provides a detailed list of proxy dispatch types (see
+[Target proxies](@ref)), as well as algorithm traits to articulate target type /scitype.
 
 
 ## Optional data interface

docs/src/operations.md

@@ -85,6 +85,8 @@ LearnAPI.IID
 | `LearnAPI.ProbabilisticSet`     | as for `Set` but labeled with probabilities (not necessarily summing to one) |
 | `LearnAPI.SurvivalFunction`     | survival function (possible requirement: observation is single-argument function mapping `Real` to `Real`) |
 | `LearnAPI.SurvivalDistribution` | probability distribution for survival time |
+| `LearnAPI.OutlierScore`         | numerical score reflecting degree of outlierness (not necessarily normalized) |
+| `LearnAPI.Continuous`           | real-valued approximation/interpolation of a discrete-valued target, such as a count (e.g., number of phone calls) |
 
 † Provided for completeness but discouraged to avoid [ambiguities in
 representation](https://github.com/alan-turing-institute/MLJ.jl/blob/dev/paper/paper.md#a-unified-approach-to-probabilistic-predictions-and-their-evaluation).

src/operations.jl

@@ -172,6 +172,8 @@ struct Set <: IID end
 struct ProbabilisticSet <: IID end
 struct SurvivalFunction <: IID end
 struct SurvivalDistribution <: IID end
+struct OutlierScore <: IID end
+struct Continuous <: IID end
 
 struct JointSampleable <: KindOfProxy end
 struct JointDistribution <: KindOfProxy end