tweak

Author: ablaom

docs/src/fit_update.md

@@ -60,7 +60,7 @@ or, if implemented, using a single call:
 transform(algorithm, X) # `fit` implied
 ```
 
-### Static algorithms (no "learning")
+### [Static algorithms (no "learning")](@id static_algorithms)
 
 Suppose `algorithm` is some clustering algorithm that cannot be generalized to new data
 (e.g. DBSCAN):

docs/src/reference.md

@@ -148,9 +148,9 @@ bare minimum implementation, see the implementation of `SmallAlgorithm`
 ### List of methods
 
 - [`fit`](@ref fit): for training or updating algorithms that generalize to new data. Or,
-  for non-generalizing algorithms (see [Static Algorithms](@ref)), for wrapping
-  `algorithm` in a mutable struct that can be mutated by `predict`/`transform` to record
-  byproducts of those operations.
+  for non-generalizing algorithms (see [here](@ref static_algorithms) and [Static
+  Algorithms](@ref)), for wrapping `algorithm` in a mutable struct that can be mutated by
+  `predict`/`transform` to record byproducts of those operations.
 
 - [`update`](@ref fit): for updating learning outcomes after hyperparameter changes, such
   as increasing an iteration parameter.