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Number of
instances with
noise
Number of
noisy
instances
Number of
common noisy
instances
Number of
instances
without noise
Total noise
Attribute
Temperature 1
4600
62
4510
15
90
Temperature 2
4600
43
4510
Table 1. The Number of the Italy dataset instances with and without noise
Table 1 shows that the number of the noisy data in the attribute Temperature 1 is 62 and this
is 43 for the attribute Temperature 2; 15 noise instances are common among the attributes
Temperature 1 and Temperature 2, and thus the total instances for two attributes after
removing noise is 4510. It means:
4600-(62+43)-15=4510
After removing the noise from the dataset, the Fuzzy C-Mean clustering (FCM) was used to
detect the outliers and extract the desired data.
The FCM was used to cluster the data after removing the noisy data to mine the desired
cluster. The noise detected in the present study was found to have effect on the FCM, and
the mean is not defined well due to the noise. Therefore, the noisy data must be removed in
order to get the accurate results.
Fig. 4. Detecting and Clustering Outliers on Italy Dataset.
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