Some Similarity Measures of Neutrosophic Sets Based on the Euclidean Distance and Their Application in Medical Diagnosis

Table 1

The relation between the diagnosis and the symptom for SVNS decision information.

	<0.4, 0.6, 0.0>	<0.3, 0.2, 0.5>	<0.1, 0.3, 0.7>	<0.4, 0.3, 0.3>	<0.1, 0.2, 0.7>
	<0.7, 0.3, 0.0>	<0.2, 0.2, 0.6>	<0.0, 0.1, 0.9>	<0.7, 0.3, 0.0>	<0.1, 0.1, 0.8>
	<0.3, 0.4, 0.3>	<0.6, 0.3, 0.1>	<0.2, 0.1, 0.7>	<0.2, 0.2, 0.6>	<0.1, 0.0, 0.9>
	<0.1, 0.2, 0.7>	<0.2, 0.4, 0.4>	<0.8, 0.2, 0.0>	<0.2, 0.1, 0.7>	<0.2, 0.1, 0.7>
	<0.1, 0.1, 0.8>	<0.0, 0.2, 0.8>	<0.2, 0.0, 0.8>	<0.2, 0.0, 0.8>	<0.8, 0.1, 0.1>

We can calculate the similarity measures and , and then the diagnoses of the patient can be classified by .