From edf4357ebcf7e71313b1c067afe60f5ea8aee066 Mon Sep 17 00:00:00 2001
From: sbosse <sbosse@uni-bremen.de>
Date: Tue, 27 Aug 2024 00:16:12 +0200
Subject: [PATCH] Tue 27 Aug 00:14:56 CEST 2024

---
 test/test-knn2.js | 51 +++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 51 insertions(+)
 create mode 100644 test/test-knn2.js

diff --git a/test/test-knn2.js b/test/test-knn2.js
new file mode 100644
index 0000000..f4b133c
--- /dev/null
+++ b/test/test-knn2.js
@@ -0,0 +1,51 @@
+var dataset = [
+  {a: 1, b:2, y: 2},
+  {a: 3, b:1, y: 4},
+  {a: 5, b:2, y: 6},
+  {a: 7, b:1, y: 8},
+  {a: 9, b:2, y: 0},
+];
+
+
+var model = ml.learn({
+  algorithm:ml.ML.KNN2,
+  data:dataset, 
+  features : ["a","b"],
+  target : 'y'
+});
+var nearest = ml.classify(model,[{ a: 3, b:1}, { a:6, b:1}]);
+print(nearest);
+
+// Categorical datat is not supported (due to interpolation feature)!
+dataset = [
+  {a: 1, b:2, y: 'yellow'},
+  {a: 3, b:1, y: 'green'},
+  {a: 5, b:2, y: 'yellow'},
+  {a: 7, b:1, y: 'red'},
+  {a: 9, b:2, y: 'blue'},
+];
+
+model = ml.learn({
+  algorithm:ml.ML.KNN2,
+  data:dataset, 
+  features : ["a","b"],
+  target : 'y'
+});
+nearest = ml.classify(model,[{ a: 7, b:1}, { a:4, b:1}]);
+print(nearest);
+
+
+var x = [[0, 0, 0], [0, 1, 1], [1, 1, 0], [2, 2, 2], [1, 2, 2], [2, 1, 2]];
+var y = [0, 0.2, 0.4, 1, 1.2, 1.4];
+
+model = ml.learn({
+  algorithm:ml.ML.KNN2,
+  x:x, 
+  y:y,
+});
+print(toJSON(model).length+' Bytes')
+
+var test_data =[[0, 1, 0],
+                [2, 2, 3]];
+
+print(ml.classify(model,test_data))