Well, in the context of machine learning classification problem, it is a performance measurement where output can be two or more classes. It is a table with 4 different combinations of predicted and actual values.
It is well explained in the following link, "https://towardsdatascience.com/understanding-confusion-matrix-a9ad42dcfd62". I hope it helps.
The confusion matrix is a 2×2 table that contains 4 outputs provided by the binary classifier . Various measures, such as error - rate, accuracy, specificity, sensitivity, precision and recall are derived from it Confusion Matrix.
Thank you very much for your valuable ideas Dr. Arnab Chatterjee .
Thank you very much for your valuable ideas Dr. Thaer Dawood Salman .
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 confusin
DescriptionIn the field of machine learning and specifically the problem of statistical classification, a confusion matrix, also known as an error matrix, is a specific table layout that allows visualization of the performance of an algorithm, typically a supervised learning one.
A Confusion matrix is an N x N matrix used for evaluating the performance of a classification model, where N is the number of target classes. The matrix compares the actual target values with those predicted by the machine learning model. ... The rows represent the predicted values of the target variable.
Each row of the matrix represents the instances in a predicted class while each column represents the instances in an actual class (or vice versa). ... The name stems from the fact that it makes it easy to see if the system is confusing two classes (i.e. commonly mislabeling one as another).
المصفوفة هي عبارة عن نتائج الارتباطات البينية بين القيم التي تعاملنا معها وتعطي قراءات تبين مدى الارتباط ان كان معنوي او غير معنوي وان كان بالاتجاه السالبا او الموجب وغاليا ما تترتب هذه النتائج بشكل قطري وتقراء من اتجاهين والاتجاهان يعطيان نفس القراءات ونفس الدلائل
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.
I am attaching an example of confusion matrix here, hope it will help you.
Good Morning
Confusion matrices are used to visualize important predictive analytics like recall, specificity, accuracy, and precision. Confusion matrices are useful because they give direct comparisons of values like True Positives, False Positives, True Negatives and False Negative
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