Assume that you have designed a convolutional neural network for a binary classification task. In the last layer of your network, you apply the ReLU() as the none-linear function and then use the sigmoid function to compute the class probability. If the class probability is greater than/equal to 0.5 you consider the label as positive and otherwise as negative. Your dataset contains 1000 samples, where 80% of samples are positive and 20% of samples are negative. Given the specifications of this neural network, what are the precision and recall for this classifier