Question: Linear discriminant analysis Model results. accuracy: 71.11% true Moderate true Mild true No Damage true Severe class precision pred. Moderate 29 5 0 5 74.36%

Linear discriminant analysis Model results.

accuracy: 71.11%

true Moderate true Mild true No Damage true Severe class precision
pred. Moderate 29 5 0 5 74.36%
pred. Mild 0 0 1 0 0.00%
pred. No Damage 0 2 3 0 60.00%
pred. Severe 0 0 0 0 0.00%
class recall 100.00% 0.00% 75.00% 0.00%

k-Nearest Neighbors model results.

accuracy: 88.89%

true Moderate true Mild true No Damage true Severe class precision
pred. Moderate 28 0 0 1 96.55%
pred. Mild 0 6 2 0 75.00%
pred. No Damage 0 1 2 0 66.67%
pred. Severe 1 0 0 4 80.00%
class recall 96.55% 85.71% 50.00% 80.00%

Nave Bayes model results

accuracy: 51.11%

true Moderate true Mild true No Damage true Severe class precision
pred. Moderate 12 0 1 1 85.71%
pred. Mild 12 5 1 0 27.78%
pred. No Damage 0 2 2 0 50.00%
pred. Severe 5 0 0 4 44.44%
class recall 41.38% 71.43% 50.00% 80.00%

Based on the information above

  • Interpret the accuracy of each model.
  • Which of the models is the best based on accuracy?

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