MultilayerPerceptron cls = (MultilayerPerceptron) weka.core.SerializationHelper.read("c:\\MODELO\\modelocerto.model");

            Instances datapredict = new Instances(
            new BufferedReader(
            new FileReader("C:\\Users\\jvrei\\Desktop\\teste.arff")));

            datapredict.setClassIndex(datapredict.numAttributes() -1);
            Instances predicteddata = new Instances(datapredict);
            StringBuffer predsBuffer = new StringBuffer();

            for (int i = 0; i < datapredict.numInstances(); i++) {
            double clsLabel = cls.classifyInstance(datapredict.instance(i));
            String pred2 = datapredict.classAttribute().value((int) clsLabel);
            predicteddata.instance(i).setClassValue(pred2);
            }

                plainText.setHeader(datapredict);
                plainText.setBuffer(predsBuffer);
            eval.evaluateModel(cls, datapredict, plainText);
            System.out.println(eval.toSummaryString());
            System.out.println(predsBuffer.toString());