Posted On: Apr 02, 2020
Confusion Matrix, also known as the error matrix, is a table to describe the performance of the classification model on the set of test data. The rows in this table represent the predicted class while the column presents the actual class. In this table, the number of correct and incorrect predictions are described with the count values so we can get insights into the errors and the type of errors made.
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Supervised and unsupervised are the two types of Machine learning algorithms available. In the supervised type, the algorithms are applied to the known labeled data to formulate a model. Labeled data...