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Advances, Systems and Applications

Table 4 The trained model \(p(\mathbf {C}|\mathbf {T})\) with equivalent of TF-IDF vector \(\mathtt {tfidf}(\mathbf {S},\mathbf {C})\) for the training data. \(\mathbf {S} =\{ \mathbf {aa},\mathbf {ab},\mathbf {ba},\mathbf {bb} \}\) is the SFA words and \(\mathbf {C}=\{C_1,C_2,C_3 \}\) is three states of the fan

From: Fog computing application of cyber-physical models of IoT devices with symbolic approximation algorithms

Class

\(C_1\)

\(C_2\)

\(C_3\)

\(\mathbf {aa}\)

3.5649

3.1972

2.9459

\(\mathbf {ab}\)

3.5649

2.9459

2.3862

\(\mathbf {ba}\)

3.5649

3.3025

2.0986

\(\mathbf {bb}\)

3.6390

3.3025

2.3862