# Classification Performance of Thresholding Methods in the Mahalanobis-Taguchi System
## 4 Datasets
### Medical Diagnosis of Liver Disease Data  
Liver disease data represent a dataset that was originally collected and used for MTS analysis by Dr. [PERSON] himself during his initial work on MTS. These data can be considered as renowned data when it comes to evaluating MTS performances since it has been applied by various researchers in evaluating and analysing MTS performances in binary classification problems [23; 26; 30].  
The story behind the data came over nearly 30 years ago when Dr. [PERSON] working together with Dr. [PERSON] of Tokyo Tenshin Hospital on which they embarked on a joint study of liver disease diagnosis. The result of the study was made public in 1987 and the data were published in various publications as well as being used for several MTS-comparison study purposes. The data contain observations of a healthy group as well as the abnormal on 17 features as shown in Table 6.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**S.No** & **Variables** & **Notation** & **Notation for Analysis** \\ \hline
1 & Age & & X\({}_{1}\) \\ \hline
2 & Sex & & X\({}_{2}\) \\ \hline
3 & Total protein in blood & TP & X\({}_{3}\) \\ \hline
4 & Albumin in blood & Alb & X\({}_{4}\) \\ \hline
5 & Cholinesterase & Che & X\({}_{5}\) \\ \hline
6 & Glutamate O transaminase & GOT & X\({}_{6}\) \\ \hline
7 & Glutamate P transaminase & GPT & X\({}_{7}\) \\ \hline
8 & Lactate dehydrogenase & LHD & X\({}_{8}\) \\ \hline
9 & Alkanline phosphatase & Alp & X\({}_{9}\) \\ \hline
10 & r-Glutamy transpeptidase & r-GPT & X\({}_{10}\) \\ \hline
11 & Leucine aminopeptidase & LAP & X\({}_{11}\) \\ \hline \hline \end{tabular}
\end{table}
Table 6: Variables in the liver disease diagnosis and notations for the analysis.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Dataset** & **No. of Original** & **No. of Training Data** & & **No. of Testing Data** \\  & **Variables** & **Normal** & **Abnormal** & **Normal** & **Abnormal** \\ \hline
1 & Appendicitis & 7 & 42 & 10 & 43 & 11 \\
2 & Banana & 2 & 1188 & 1462 & 1188 & 1462 \\
3 & Bupa & 6 & 100 & 72 & 100 & 73 \\
4 & Coil2000 & 85 & 4618 & 293 & 4618 & 293 \\
5 & Haberman-2 & 3 & 112 & 40 & 113 & 41 \\
6 & Heart & 13 & 75 & 60 & 75 & 60 \\
7 & Ionosphere & 32 & 112 & 63 & 113 & 63 \\
8 & Magic & 10 & 6166 & 3344 & 6166 & 3344 \\
9 & Monk2 & 6 & 102 & 114 & 102 & 114 \\
10 & Phoneme & 5 & 1909 & 793 & 1909 & 793 \\
11 & Pima & 8 & 250 & 134 & 250 & 134 \\
12 & Ring & 20 & 1868 & 1832 & 1868 & 1832 \\
13 & Sonar & 60 & 65 & 48 & 46 & 49 \\
14 & Spambase & 57 & 1392 & 906 & 1393 & 906 \\
15 & Spectfheart & 44 & 106 & 27 & 106 & 28 \\
16 & Titanic & 3 & 745 & 355 & 745 & 356 \\
17 & Wdbc & 30 & 178 & 106 & 179 & 106 \\
18 & Wisconsin & 9 & 222 & 119 & 222 & 120 \\
19 & Medical Diagnosis of Liver Disease & 17 & 200 & 17 & 43 & 34 \\
20 & Taguchi Character Recognition & 14 & 16 & 9 & 2 & 37 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Twenty datasets used in this study.  
The healthy group (MS) is constructed based on observations of 200 people (healthy), who do not have any health problems together with 17 abnormal conditions (unhealthy). These data act as the training data for the construction of Mahalanobis Space MS (reference group). While a total of 60 samples (other than the training samples) are taken as the testing samples [38].