Doc: Add constant column for LSVM normalization

Pivotal Tracker: #62182584

methods/kernel_machines/src/pg_gp/online_sv.sql_in

@@ -144,7 +144,8 @@ lsvm_classification( input_table,
 Note that, as any gradient descent methods, IGD will converge with a greater
 eta (stepsize), thus faster, if the input training data is well-conditioned.
 We highly recommend user to perform data preparation, such that the mean value
-of each feature column is 0 and standard error is 1. We plan to provide a
+of each feature column is 0 and standard error is 1, and append an extra
+feature with constant value 1 for intercept term. We plan to provide a
 function for this when this module graduates from early stage development.
 
 - Learn linear or non-linear SVM(s) using the method described in [1].