35 lines
1.0 KiB
JavaScript
35 lines
1.0 KiB
JavaScript
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var data = load('test-data-iris.json')
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var t0=time()
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var target = "species";
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var features = ["length", "width","petal_length","petal_width"];
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var datac = ml.preprocess(data,'xy',{features:features,target:target});
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var model = ml.learn({
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algorithm:ml.ML.ID3,
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data:data,
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target:target,
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features:features
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})
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var t1=time()
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var result = ml.classify(model,datac.x).map(function (r,i) {
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return {value:r,y:datac.y[i]}} )
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var t2=time()
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var correct=0,wrong=0;
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result.forEach(function (r) { if (r.value==r.y) correct++; else wrong++ });
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print('Training Data Test: Correct='+correct+', wrong='+wrong);
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print(toJSON(model).length)
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print(t1-t0,t2-t1)
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datac.x = ml.noise(datac.x,
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{length:0.2,
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width:0.1,
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petal_length:0.05,
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petal_width:0.01
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});
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// print(datac.x)
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var result = ml.classify(model,datac.x).map(function (r,i) {
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return {value:r,y:datac.y[i]}} )
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correct=0,wrong=0;
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result.forEach(function (r) { if (r.value==r.y) correct++; else wrong++ });
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print('Test Data Test (Noise): Correct='+correct+', wrong='+wrong);
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