From efab1d08b2730c30e5d762fc4ee38125c96ab313 Mon Sep 17 00:00:00 2001
From: Pierre Alexandre Tremblay <info@pierrealexandretremblay.com>
Date: Fri, 17 Jul 2020 21:00:45 +0100
Subject: [PATCH] MLPregressor: corrected the helpfiles and toy example for the
 new parameter in the list

---
 .../Examples/dataset/MLP-synth-control.scd            |  4 ++--
 .../Examples/dataset/MLP-toy-example.scd              |  2 +-
 .../HelpSource/Classes/FluidMLPRegressor.schelp       | 11 ++++-------
 3 files changed, 7 insertions(+), 10 deletions(-)

diff --git a/release-packaging/Examples/dataset/MLP-synth-control.scd b/release-packaging/Examples/dataset/MLP-synth-control.scd
index 7d832a5..7d24b00 100644
--- a/release-packaging/Examples/dataset/MLP-synth-control.scd
+++ b/release-packaging/Examples/dataset/MLP-synth-control.scd
@@ -4,7 +4,7 @@ var trained = 0, entering = 0;
 var va = Array.fill(10,{0.5});
 var input = Buffer.alloc(s,2);
 var output = Buffer.alloc(s,10);
-var mlp = FluidMLPRegressor(s,[6],1,1000,0.1,0,1,0);
+var mlp = FluidMLPRegressor(s,[6],1,0,1000,0.1,0,1,0);
 var entry = 0;
 
 ~inData = FluidDataSet(s,\indata);
@@ -31,7 +31,7 @@ f.action = {arg x,y; //if trained, predict the point f.x f.y
 	}, { //if not entering a point
 		if (trained == 1, { //if trained
 			input.setn(0, [f.x, f.y]);
-			mlp.predictPoint(input,output,0,{
+			mlp.predictPoint(input,output,{
 				output.getn(0,10,{
 					|x|va = x; b.set(\val, va); {a.value = va;}.defer;});
 			});
diff --git a/release-packaging/Examples/dataset/MLP-toy-example.scd b/release-packaging/Examples/dataset/MLP-toy-example.scd
index 79fabf2..6d5dd37 100644
--- a/release-packaging/Examples/dataset/MLP-toy-example.scd
+++ b/release-packaging/Examples/dataset/MLP-toy-example.scd
@@ -26,7 +26,7 @@ Routine{
 ~mlpHelpTarget.print
 
 // make an MLPregressor
-~mlp = FluidMLPRegressor(s,[3],FluidMLPRegressor.sigmoid,1000,0.1,0.1,1,0);//1000 epoch at a time
+~mlp = FluidMLPRegressor(s, [3], FluidMLPRegressor.sigmoid, 0, 1000,0.1,0.1,1,0);//1000 epoch at a time
 //train on it and observe the error
 ~mlp.fit(~mlpHelpSource,~mlpHelpTarget,{|x|x.postln;});
 
diff --git a/release-packaging/HelpSource/Classes/FluidMLPRegressor.schelp b/release-packaging/HelpSource/Classes/FluidMLPRegressor.schelp
index ed92fa0..cb7da81 100644
--- a/release-packaging/HelpSource/Classes/FluidMLPRegressor.schelp
+++ b/release-packaging/HelpSource/Classes/FluidMLPRegressor.schelp
@@ -20,6 +20,9 @@ An link::Classes/Array:: that gives the sizes of any hidden layers in the networ
 ARGUMENT:: activation
 The activation function to use for the hidden layer units.
 
+ARGUMENT:: outputLayer
+The layer whose output to return. It is negative 0 counting, where the default of 0 is the output layer, and 1 would be the last hidden layer, and so on.
+
 ARGUMENT:: maxIter
 The maximum number of iterations to use in training.
 
@@ -65,9 +68,6 @@ Input data
 ARGUMENT:: targetDataSet
 Output data
 
-ARGUMENT:: layer
-Layer whose output to return.
-
 ARGUMENT:: action
 Function to run when complete
 
@@ -80,9 +80,6 @@ Input point
 ARGUMENT:: targetBuffer
 Output point
 
-ARGUMENT:: layer
-Layer whose output to return.
-
 ARGUMENT:: action
 A function to run when complete
 
@@ -103,7 +100,7 @@ code::
 ~test = FluidDataSet(s,\mlp_regressor_dest);
 ~output = FluidDataSet(s,\mlp_regress_out);
 ~tmpbuf = Buffer.alloc(s,1);
-~regressor = FluidMLPRegressor(s,[2],FluidMLPRegressor.tanh,1000,0.1,0.1,1,0);
+~regressor = FluidMLPRegressor(s,[2], FluidMLPRegressor.tanh, 0, 1000,0.1,0.1,1,0);
 )
 
 //Make source, target and test data