Memory management in Python involves a private heap containing all Python objects and data structures. The management of this private heap is ensured internally by the Python memory manager. The Python memory manager has different components which deal with various dynamic storage management aspects, like sharing, segmentation or preallocation. If some contents or data doesn't used by user for a long time it is deleted by garbage collector provided by Python.
Classification work on voting the object belongs from which classes has more probability There are two types of classification : Binary classification : There are two classes we have ex: male-female , cat-dog , yes-not Multiple classification : There are classes more than two we have ex: traffic signs , face recognition , flower race , Digit Recognition Confusion matrix : Confusion matrix is one type of technique to evaluate the model accuracy for classification problem. In this technique we consider how many of positive and negative data points we predict correctly. The main consideration terms are accuracy, precision and recall The accuracy was an appealing matric, because it was a single number. Here precision and recall(sensitivity) are two numbers. So to get the final score (accuracy) of our model we use F1 score, so that we have a single number. Here is the F1 score's mathematical formula: F1 = 2x precision x recall / (precision ...
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