// Test 1
var training_data = [
  	{"color":"blue", "shape":"square", "liked":false},
  	{"color":"red", "shape":"square",  "liked":false},
  	{"color":"blue", "shape":"circle", "liked":true},
  	{"color":"red", "shape":"circle", "liked":true},
  	{"color":"blue", "shape":"hexagon", "liked":false},
  	{"color":"red", "shape":"hexagon", "liked":false},
  	{"color":"yellow", "shape":"hexagon", "liked":true},
  	{"color":"yellow", "shape":"circle", "liked":true}
]

var test_data = [
  	{"color":"blue", "shape":"hexagon", "liked":false},
  	{"color":"red", "shape":"hexagon", "liked":false},
  	{"color":"yellow", "shape":"hexagon", "liked":true},
  	{"color":"yellow", "shape":"circle", "liked":true}
  ];

var target = "liked";
var features = ["color", "shape"];
var model = ml.learn({
 algorithm:ml.ML.C45,
 data:training_data,
 target:target,
 features:features
})

print(ml.print(model))
print(toJSON(model).length+' Bytes')
print(ml.classify(model,test_data))

// Test 2
var A='A',B='B',C='C',False=false,True=true,CLASS1='CLASS1',CLASS2='CLASS2';
training_data = [
[A,70,True,CLASS1],
[A,90,True,CLASS2],
[A,85,False,CLASS2],
[A,95,False,CLASS2],
[A,70,False,CLASS1],
[B,90,True,CLASS1],
[B,78,False,CLASS1],
[B,65,True,CLASS1],
[B,75,False,CLASS1],
[C,80,True,CLASS2],
[C,70,True,CLASS2],
[C,80,False,CLASS1],
[C,80,False,CLASS1],
[C,96,False,CLASS1],
]

test_data = [
  [B,71,False],
  [C,70,True],
]
      
model = ml.learn({
 algorithm:ml.ML.C45,
 data:training_data
})


print(ml.print(model))
print(ml.classify(model,test_data))

