Confusion matrix:
The confusion matrix is a matrix used to determine the performance of the
classification models for a given set of test data. It can only be determined if
the true values for test data are known. The matrix itself can be easily
understood, but the related terminologies may be confusing. Since it shows
the errors in the model performance in the form of a matrix, hence also
known as an error matrix. Some features of Confusion matrix are given
below:
o For the 2 prediction classes of classifiers, the matrix is of 2*2 table, for
3 classes, it is 3*3 table, and so on.
o The matrix is divided into two dimensions, that are predicted
values and actual values along with the total number of predictions.
o Predicted values are those values, which are predicted by the model,
and actual values are the true values for the given observations.
o It looks like the below table:
The confusion matrix is a matrix used to determine the performance of the
classification models for a given set of test data. It can only be determined if
the true values for test data are known. The matrix itself can be easily
understood, but the related terminologies may be confusing. Since it shows
the errors in the model performance in the form of a matrix, hence also
known as an error matrix. Some features of Confusion matrix are given
below:
o For the 2 prediction classes of classifiers, the matrix is of 2*2 table, for
3 classes, it is 3*3 table, and so on.
o The matrix is divided into two dimensions, that are predicted
values and actual values along with the total number of predictions.
o Predicted values are those values, which are predicted by the model,
and actual values are the true values for the given observations.
o It looks like the below table:
