diff --git a/doc/source/init.md b/doc/source/init.md
index 3e114836..e3914302 100644
--- a/doc/source/init.md
+++ b/doc/source/init.md
@@ -23,18 +23,12 @@ KmppAlg
 KmCentralityAlg
 RandSeedAlg
 ```
+In practice, we have found that *Kmeans++* is the most effective choice.
 
-For convenience, the package also defines the two wrapper methods that take
-the name of the seeding algorithm and the number of clusters and take care of
-allocating `iseeds` and applying the proper `SeedingAlgorithm` instance:
+For convenience, the package defines the two wrapper functions that accept
+the short name of the seeding algorithm and the number of clusters and take
+care of allocating `iseeds` and applying the proper `SeedingAlgorithm`:
 ```@docs
 initseeds
 initseeds_by_costs
 ```
-
-In practice, we found that *Kmeans++* is the most effective seeding method. To
-simplify its usage we provide:
-```@docs
-kmpp
-kmpp_by_costs
-```
diff --git a/src/deprecate.jl b/src/deprecate.jl
index cf070776..3e3ce017 100644
--- a/src/deprecate.jl
+++ b/src/deprecate.jl
@@ -1,2 +1,5 @@
 ## Deprecated
 
+# deprecated at 0.13
+@deprecate kmpp(X, k) initseeds(:kmpp, X, k)
+@deprecate kmpp_by_costs(costs, k) initseeds_by_costs(:kmpp, costs, k)
diff --git a/src/seeding.jl b/src/seeding.jl
index 958b11a4..fd00e176 100644
--- a/src/seeding.jl
+++ b/src/seeding.jl
@@ -201,21 +201,6 @@ function initseeds_by_costs!(iseeds::IntegerVector, alg::KmppAlg,
     return iseeds
 end
 
-"""
-    kmpp(X, k)
-
-Use *Kmeans++* to choose `k` seeds from the ``d×n`` data matrix `X`.
-"""
-kmpp(X::AbstractMatrix{<:Real}, k::Int) = initseeds(KmppAlg(), X, k)
-
-"""
-    kmpp_by_costs(C, k)
-
-Use *Kmeans++* to choose `k` seeds based on the ``n×n`` cost matrix `C`.
-"""
-kmpp_by_costs(costs::AbstractMatrix{<:Real}, k::Int) = initseeds(KmppAlg(), costs, k)
-
-
 """
 K-medoids initialization based on centrality (`:kmcen`).
 
diff --git a/test/seeding.jl b/test/seeding.jl
index 8cd638ca..9d5fac1a 100644
--- a/test/seeding.jl
+++ b/test/seeding.jl
@@ -81,19 +81,19 @@ end
     @test min_interdist((Xt')[:, iseeds]) > 20 * md0
 
     Random.seed!(34568)
-    iseeds = kmpp(X, k)
+    iseeds = initseeds(:kmpp, X, k)
     @test length(iseeds) == k
     @test alldistinct(iseeds)
     Random.seed!(34568)
-    iseeds_t = kmpp(Xt', k)
+    iseeds_t = initseeds(:kmpp, Xt', k)
     @test iseeds_t == iseeds
 
     Random.seed!(34568)
-    iseeds = kmpp_by_costs(C, k)
+    iseeds = initseeds_by_costs(:kmpp, C, k)
     @test length(iseeds) == k
     @test alldistinct(iseeds)
     Random.seed!(34568)
-    iseeds_t = kmpp_by_costs(Ct', k)
+    iseeds_t = initseeds_by_costs(:kmpp, Ct', k)
     @test iseeds_t == iseeds
 end