Machine Learnig (Estatística (confusion matrix (classification problem)…
confusion matrix (classification problem)
Accuracy should NEVER be used as a measure when the target variable classes in the data are a majority of one class.
Accuracy is a good measure when the target variable classes in the data are nearly balanced.
Precision is about being precise. So even if we managed to capture only one cancer case, and we captured it correctly, then we are 100% precise.
Recall or Sensitivity
Recall is not so much about capturing cases correctly but more about capturing all cases that have “cancer” with the answer as “cancer”. So if we simply always say every case as “cancer”, we have 100% recall.
Specificity is the exact opposite of Recall.
Precision x Recall
F1 Score = Harmonic Mean(Precision, Recall)
Probability Mass Function (PMF) Discrete
Probability Density Function (PDF) Continuous
Expected Value :warning:
Keras & Tensor Flow