True positives, False positives, Confusion matrix, Recall, Precision, Accuracy. These terms have been eating the heads of any beginner machine learning enthusiast for some time. This is an attempt to simplify those parameters that are crucial in determining the performance of a binary classification model. A binary classification model is an algorithm used to predict the probability of occurrence of an event( i.e, either the event will happen or it will not). It is binary because there are only two possibilities(either yes or no). These performance calculating matrices maybe used in higher level classification algorithms(more than two possibilities of classification)…

Ligin Saju George

Machine Learning Professional, Doesn't write to live but would love to!

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