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med:lab_5 [2018/05/12 23:19] pszwed [Kod] |
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- | ====== Metody Eksploracji Danych: Laboratorium 5 ====== | ||
- | Podczas zajęć będziemy korzystali z funkcji biblioteki Weka wołanych programowo z kodu Java. | ||
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- | {{: | ||
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- | Zapoznaj się z treścią | ||
- | *{{: | ||
- | *{{: | ||
- | *{{: | ||
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- | ===== Zbiory danych ===== | ||
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- | [[http:// | ||
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- | ===== Weka ===== | ||
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- | Brak specjalnych wymagań | ||
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- | ===== IDE ===== | ||
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- | * W '' | ||
- | * Utwórz projekt | ||
- | * Wybierz: //Project -> Properties -> Java Build Path.// Następnie zakładkę // | ||
- | ===== Kod ===== | ||
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- | Fragmenty kodu: | ||
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- | <code java> | ||
- | DataSource source = new DataSource(" | ||
- | Instances data = source.getDataSet(); | ||
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- | if (data.classIndex() == -1) | ||
- | data.setClassIndex(data.numAttributes() - 1); | ||
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- | </ | ||
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- | Utworznenie i uczenie klasyfikatora | ||
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- | <code java> | ||
- | Classifier cls = new NaiveBayes(); | ||
- | cls.buildClassifier(data); | ||
- | </ | ||
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- | Instancja do sklasyfikowania | ||
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- | <code java> | ||
- | Instance inst = new DenseInstance (3); | ||
- | inst.setDataset (data); | ||
- | inst.setValue(0, | ||
- | inst.setValue(1, | ||
- | </ | ||
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- | <code java> | ||
- | double[] distrib = cls.distributionForInstance(inst); | ||
- | System.out.printf(Locale.US," | ||
- | </ | ||
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- | |||
- | <code java> | ||
- | List< | ||
- | new Attribute(" | ||
- | new Attribute(" | ||
- | new Attribute(" | ||
- | | ||
- | Instances result = new Instances(" | ||
- | result.setClassIndex(result.numAttributes()-1); | ||
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- | </ | ||
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- | <code java> | ||
- | for(double x1=-10; | ||
- | | ||
- | Instance inst = new DenseInstance(3); | ||
- | inst.setValue(0, | ||
- | inst.setValue(1, | ||
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- | inst.setDataset(result); | ||
- | double y = cls.classifyInstance(inst); | ||
- | inst.setClassValue(y); | ||
- | result.add(inst); | ||
- | } | ||
- | } | ||
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- | </ |