Transfer Learning-Based Condition Monitoring of Single Point Cutting Tool

Table 5

Performance comparison with state-of-the-art techniques.

Classifier	Classification accuracy (%)	Reference
Bayes Net	86.34	[42]
Naïve Bayes	85.28
Decision tree	77.22	[39]
K-Star	78.00	[43]
v-SVC	88.06	[44]
C-SVC	87.50
Proposed methodology	91.90

The value depicted in bold represents the best classification accuracy produced in comparison with other state-of-the-art techniques. The proposed method delivers the highest classification accuracy than the other techniques investigated in the literature.