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Table 3 Confusion matrices for Binary Decision Tree, Random Forest, and Support Vector Machine classifiers trained on hip data

From: Machine learning algorithms for activity recognition in ambulant children and adolescents with cerebral palsy

Activity Class

Binary Decision Tree

Observed

Prediction

SED

SUM

CW

BW

 1. SED

1294 [0.95]

70 [0.05]

0 [0.00]

0 [0.00]

 2. SUM

149 [0.11]

1138 [0.83]

72 [0.05]

5 [0.00]

 3. CW

7 [0.01]

57 [0.07]

534 [0.69]

179 [0.23]

 4. BW

17 [0.01]

66 [0.04]

255 [0.16]

1216 [0.78]

Random Forest

 1. SED

1304 [0.96]

59 [0.04]

1 [0.00]

0 [0.00]

 2. SUM

127 [0.09]

1193 [0.87]

26 [0.02]

18 [0.01]

 3. CW

7 [0.01]

65 [0.08]

471 [0.61]

234 [0.30]

 4. BW

16 [0.01]

51 [0.03]

168 [0.11]

1319 [0.85]

Support Vector Machine

 1. SED

1310 [0.96]

51 [0.04]

1 [0.00]

2 [0.00]

 2. SUM

149 [0.11]

1138 [0.83]

72 [0.05]

5 [0.00]

 3. CW

7 [0.01]

57 [0.07]

534 [0.69]

179 [0.23]

 4. BW

18 [0.01]

47 [0.03]

188 [0.12]

1301 [0.84]

  1. Numbers represent observation counts. Percentage of observations for a given class reported in brackets. Values in bold face indicate number and proportion of observations within each class correctly classified
  2. SED sedentary, SUM standing utilitarian movements, CW comfortable walk, BW brisk walk