add links to classifier exemplar; fix some links

Author: ablaom

README.md

@@ -13,7 +13,7 @@ New contributions welcome. See the [road map](ROADMAP.md).
 
 ## Synopsis
 
-Package provides for variations and elaborations on the following basic pattern in machine
+LearnAPI.jl provides for variations and elaborations on the following basic pattern in machine
 learning and statistics:
 
 ```julia
@@ -30,7 +30,7 @@ Here `learner` specifies the configuration the algorithm (the hyperparameters) w
 
 - [LearnTestAPI.jl](https://github.com/JuliaAI/LearnTestAPI.jl): Package to test implementations of LearnAPI.jl (but documented here)
 
-- [LearnDataFrontEnds.jl](https://github.com/JuliaAI/LearnDataFrontEnds.jl): for including flexible, user-friendly, data front ends for LearnAPI.jl implementations ([docs]((https://juliaai.github.io/stable/))
+- [LearnDataFrontEnds.jl](https://github.com/JuliaAI/LearnDataFrontEnds.jl): for including flexible, user-friendly, data front ends for LearnAPI.jl implementations ([docs](https://juliaai.github.io/stable/))
 
 
 ## Credits

docs/src/patterns/classification.md

@@ -2,4 +2,6 @@
 
 See these examples from the JuliaTestAPI.jl test suite:
 
-- [perceptron classifier](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/test/patterns/gradient_descent.jl)
+- [perceptron classifier](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/gradient_descent.jl)
+
+- [constant classifier](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/classification.jl) (including `Sage` data front end)

docs/src/patterns/density_estimation.md

@@ -2,4 +2,4 @@
 
 See these examples from the JuliaTestAPI.jl test suite:
 
-- [normal distribution estimator](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/test/patterns/incremental_algorithms.jl)
+- [normal distribution estimator](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/incremental_algorithms.jl)

docs/src/patterns/dimension_reduction.md

@@ -2,5 +2,5 @@
 
 See these examples from the JuliaTestAPI.jl test suite:
 
-- [Truncated SVD](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/test/patterns/dimension_reduction.jl)
+- [Truncated SVD](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/dimension_reduction.jl) (including `Tarragon` data front end)
 

docs/src/patterns/ensembling.md

@@ -2,6 +2,6 @@
 
 See these examples from the JuliaTestAPI.jl test suite:
 
-- [bagged ensembling of a regression model](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/test/patterns/ensembling.jl)
+- [bagged ensembling of a regression model](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/ensembling.jl)
 
-- [extremely randomized ensemble of decision stumps (regression)](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/test/patterns/ensembling.jl)
+- [extremely randomized ensemble of decision stumps (regression)](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/ensembling.jl)

docs/src/patterns/feature_engineering.md

@@ -3,5 +3,5 @@
 See these examples from the JuliaTestAI.jl test suite:
 
 - [feature
-  selectors](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/test/patterns/static_algorithms.jl)
+  selectors](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/static_algorithms.jl)
   from tests.

docs/src/patterns/gradient_descent.md

@@ -2,4 +2,4 @@
 
 See these examples from the JuliaTestAI.jl test suite:
 
-- [perceptron classifier](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/test/patterns/gradient_descent.jl)
+- [perceptron classifier](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/gradient_descent.jl)

docs/src/patterns/incremental_algorithms.md

@@ -2,4 +2,4 @@
 
 See these examples from the JuliaTestAI.jl test suite:
 
-- [normal distribution estimator](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/test/patterns/incremental_algorithms.jl)
+- [normal distribution estimator](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/incremental_algorithms.jl)

docs/src/patterns/iterative_algorithms.md

@@ -2,8 +2,8 @@
 
 See these examples from the JuliaTestAI.jl test suite:
 
-- [bagged ensembling](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/test/patterns/ensembling.jl)
+- [bagged ensembling](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/ensembling.jl)
 
-- [perceptron classifier](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/test/patterns/gradient_descent.jl)
+- [perceptron classifier](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/gradient_descent.jl)
 
-- [extremely randomized ensemble of decision stumps (regression)](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/test/patterns/ensembling.jl)
+- [extremely randomized ensemble of decision stumps (regression)](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/ensembling.jl)

docs/src/patterns/meta_algorithms.md

@@ -2,6 +2,6 @@
 
 Many meta-algorithms are can be implemented as wrappers.  An example is [this bagged
 ensemble
-algorithm](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/test/patterns/ensembling.jl)
+algorithm](https://github.com/JuliaAI/LearnTestAPI.jl/blob/dev/src/learners/ensembling.jl)
 from tests.