Confusion matrix. a confusion matrix is a table that is often used to describe the performance of a classification model (or “classifier”) on a set of test data for which the true values are known. the confusion matrix itself is relatively simple to understand, but the related terminology can be confusing. the confusion matrix shows the. 1: collect and feed the it and ipc sections of cyber crime types of existing cyber crime cases in india. 2: enclose the details of penalty and punishments of every type of cyber crime.
According to the cybercrime case study internationally, a total of 14,000 transactions were carried out, spanning across 28 countries using 450 cards. nationally, 2,800 transactions using 400 cards were carried out. this was one of its kinds, and in fact, the first malware attack that stopped all communication between the bank and the payment. A confusion matrix is the comparison summary of the predicted results and the actual results in any classification problem use case. the comparison summary is extremely necessary to determine the performance of the model after it is trained with some training data. for a binary classification use case, a confusion matrix is a 2×2 matrix which. 1: collect and feed the it and ipc sections of cyber crime types of existing cyber crime cases in india. 2: enclose the details of penalty and punishments of every type of cyber crime. 5. confusion matrix and accuracy. the confusion matrix that was obtained from the classifier is depicted in figure below. it is in normalized form, since the classes are imbalanced. the darker the blue, the better the classifier is at predicting files for this class. it is clear where the classifier gets ‘confused’.
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