Recall (also known as sensitivity) is the ratio of true positives (based on the confusion matrix) by all positives (=true positives + false negatives). It is commonly used in conjunction with precision and it is needed when we must minimize false negatives. Recall can be considered the opposite metric of specificity. Recall is a measure ... Read more
In machine learning, regularization is a method by which the ML model cost/error function is changed, to include an extra variable called the regularization hyperparameter. There are two basic types of regularization: L1-norm (lasso regression) and L2-norm (ridge regression). The Lasso regularization uses the L1 norm parameter. The lasso regularized cost function is calculated as ... Read more
The ReLU (rectified linear unit function) function is an ANN activation function which calculates a linear function of the inputs. If the result is positive, it outputs that result. If it is negative, it outputs 0. The mathematical formula for the ReLU function is f (x) = max(0, x). The graph of the ReLU function ... Read more
RMSE is simply the root of the MSE statistical metric. RMSE stands for Root Mean Squared Error. The RMSE is in the same metric scale as the observed parameters, same as the MAE metric. RMSE is a calculation for the standard deviation of residuals. Compared to RMSE, MSE is a calculation of the variance of ... Read more
