KNNClassifier / Regressor review

release-packaging/Classes/FluidKNNClassifier.sc

@@ -1,30 +1,29 @@
 FluidKNNClassifier : FluidManipulationClient {
 
 	*new {|server|
-        var uid = UniqueID.next;
+		var uid = UniqueID.next;
-        ^super.new(server,uid)!?{|inst|inst.init(uid);inst}
+		^super.new(server,uid)!?{|inst|inst.init(uid);inst}
-    }
+	}
 
-    init {|uid|
+	init {|uid|
-        id = uid;
+		id = uid;
-    }
+	}
 
-    fit{|dataset, labelset, action|
+	fit{|dataset, labelset, action|
-       this.prSendMsg(\fit,[dataset.asSymbol, labelset.asSymbol], action);
+	   this.prSendMsg(\fit,[dataset.asSymbol, labelset.asSymbol], action);
-    }
+	}
 
-    predict{ |dataset, labelset, k, uniform = 0, action|
+	predict{|dataset, labelset, k, uniform = 0, action|
-        this.prSendMsg(\predict,
+		this.prSendMsg(\predict,
 			[dataset.asSymbol, labelset.asSymbol, k, uniform],
 			action);
-    }
+	}
 
-    predictPoint { |buffer, k, uniform = 0, action|
+	predictPoint {|buffer, k, uniform = 0, action|
-        this.prSendMsg(\predictPoint,
+		this.prSendMsg(\predictPoint,
-			[buffer.asUGenInput, k,uniform], action,
+			[buffer.asUGenInput, k, uniform], action,
 			[string(FluidMessageResponse,_,_)]
 		);
 	}
 
-
 }

release-packaging/Classes/FluidKNNRegressor.sc

@@ -1,29 +1,29 @@
 FluidKNNRegressor : FluidManipulationClient {
 
 	*new {|server|
-        var uid = UniqueID.next;
+		var uid = UniqueID.next;
-        ^super.new(server,uid)!?{|inst|inst.init(uid);inst}
+		^super.new(server,uid)!?{|inst|inst.init(uid);inst}
-    }
+	}
 
-    init {|uid|
+	init {|uid|
-        id = uid;
+		id = uid;
-    }
+	}
 
-    fit{|sourceDataset, targetDataset, action|
+	fit{|sourceDataset, targetDataset, action|
-       this.prSendMsg(\fit,
+	   this.prSendMsg(\fit,
 			[sourceDataset.asSymbol, targetDataset.asSymbol],
 			action
 		);
-    }
+	}
 
-    predict{ |sourceDataset, targetDataset, k, uniform = 0, action|
+	predict{ |sourceDataset, targetDataset, k, uniform = 0, action|
-        this.prSendMsg(\predict,
+		this.prSendMsg(\predict,
 			[sourceDataset.asSymbol, targetDataset.asSymbol, k, uniform],
 			action);
-    }
+	}
 
-    predictPoint { |buffer, k, uniform = 0, action|
+	predictPoint { |buffer, k, uniform = 0, action|
-        this.prSendMsg(\predictPoint, [buffer.asUGenInput, k,uniform], action,
+		this.prSendMsg(\predictPoint, [buffer.asUGenInput, k, uniform], action,
 			[number(FluidMessageResponse,_,_)]);
-    }
+	}
 }

release-packaging/HelpSource/Classes/FluidKNNClassifier.schelp

@@ -4,6 +4,8 @@ categories:: Classification, KNN
 related:: Classes/FluidKNNRegressor, Classes/FluidDataSet, Classes/FluidLabelSet
 
 DESCRIPTION::
+A nearest-neighbor classifier using link::Classes/FluidKDTree:: . Each point is assigned the class that is most common among its nearest neighbors.
+https://scikit-learn.org/stable/modules/neighbors.html#classification
 
 CLASSMETHODS::
 
@@ -15,7 +17,7 @@ The server to make the model on
 INSTANCEMETHODS::
 
 METHOD:: fit
-Fit the model to a source link::Classes/FluidDataSet:: and a target link::Classes/FluidLabelSet:: . These need to be the sime size
+Fit the model to a source link::Classes/FluidDataSet:: and a target link::Classes/FluidLabelSet::. These need to be the same size
 ARGUMENT:: dataset
 Source data
 ARGUMENT:: labelset
@@ -32,7 +34,7 @@ place to write labels
 ARGUMENT:: k
 the number of neighours to consider
 ARGUMENT:: uniform
-true / false: whether the neighbours shold be weighted by distance
+true / false: whether the neighbours should be weighted by distance
 ARGUMENT:: action
 Run when done
 
@@ -43,7 +45,7 @@ A data point
 ARGUMENT:: k
 Number of neighbours to consider
 ARGUMENT:: uniform
-true / false: whether the neighbours shold be weighted by distance
+true / false: whether the neighbours should be weighted by distance (default) or uniformly
 ARGUMENT:: action
 Run when done, passes predicted label as argument
 

release-packaging/HelpSource/Classes/FluidKNNRegressor.schelp

@@ -4,6 +4,9 @@ categories:: Regression
 related:: Classes/FluidKNNClassifier, Classes/FluidDataSet
 
 DESCRIPTION::
+A nearest-neighbor regressor. A continuous value is predicted for each point as the (weighted) average value of its nearest neighbors.
+
+https://scikit-learn.org/stable/modules/neighbors.html#regression
 
 CLASSMETHODS::
 
@@ -15,7 +18,7 @@ The server to run this model on.
 INSTANCEMETHODS::
 
 METHOD:: fit
-Map a source link::Classes/FluidDataSet:: to a target; they must be the same size, but can have different dimensionality
+Map a source link::Classes/FluidDataSet:: to a one-dimensional target; both datasets need to have the same number of points.
 ARGUMENT:: sourceDataset
 Source data
 ARGUMENT:: targetDataset
@@ -44,7 +47,7 @@ data point
 ARGUMENT:: k
 number of neigbours to consider in mapping, min 1
 ARGUMENT:: uniform
-Whether to weight neighbours by distance when producing new point
+Whether the neighbours should be weighted by distance (default) or uniformly
 ARGUMENT:: action
 Run when done