PrologMethods/Classification/linear_svm.md

@@ -94,8 +94,7 @@ classifyPoint(  +pointer(float_array), +integer,
 ### Parameters
 | Name | Type | Description | Default |
 |------|------|-------------|---------|
-| point | +vector | Point to be classified. |  |
-| - |  |  |  |
+| point | +vector | Point to be classified. | - |
 | predictedLabel | -integer | Predicted class label of the point. | - |
 
 ---
@@ -150,7 +149,7 @@ train(  +pointer(float_array), +integer, +integer,
 
 If you want a more detailed explanation, then go to the python documentation. There is most of the time a good explanation on how the methods work and what the parameters do.
 
-* MLpack::linear_svm_C++\_documentation
+* [MLpack::linear_svm_C++\_documentation](https://www.mlpack.org/doc/stable/doxygen/classmlpack_1_1svm_1_1LinearSVM.html)
 * [MLpack::linear_svm_Python_documentation](https://www.mlpack.org/doc/stable/python_documentation.html#linear_svm)
 
 added some of the links from the python documentation