What is specificity in machine learning? Specificity is a measure in machine learning using which we can calculate the performance of a machine learning model that solves classification problems. Specificity determines how well a machine learning model can predict...
What is sensitivity in machine learning? Sensitivity in machine learning is a measure to determine the performance of a machine learning model. Sensitivity determines how well a machine learning model can predict positive instances. Before we understand the...
What is cross-entropy loss? Cross-entropy loss is a measure of performance for a classification model. If a classification model correctly predicts the class, the cross-entropy loss will be 0. And if the classification model deviates from predicting the class...
What is a Ridge classifier? A Ridge classifier is a classifier that uses Ridge regression to solve a classification problem. For example, let’s say there is a binary classification problem where the target variable can take two values. In the Ridge classifier, the...
In the Dynamic Classifier Selection (DCS), we provide a list of machine learning models. Each model is trained with the training data. When a new prediction needs to be made, we select the model that can make the best prediction. We can take the following two...
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