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Tue 27 Aug 00:14:56 CEST 2024

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commit eeb5cab5ef
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// 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))