I did a number of machine learning experiments to predict a binary classification. I measured precision, recall and accuracy.

I noticed that my precision is generally quite high, and recall and accuracy are always the same numbers.

I used the following definitions:

Precision = TP / (TP + FP)

Recall: TP / (TP + FN)

Accuracy: (TP + TN) / (P + N)

I have some difficulties to interpret accuracy and recall. What does it mean if these two number are always the same in my case?