Multiple choices questions in NLP, Natural Language Processing solved MCQ, Accuracy and precision, How does high false positive value affect precision of the prediction system? false positive is type I error, Why does a prediction system with high false positives ends up with low precision?
Natural Language Processing MCQ - Impact of FALSE POSITIVE on the system's precision mesure
1. A classifier that makes a lot of FALSE POSITIVEs will have ________.
a) Low recall
b) Low precision
c) High recall
d) High precision
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Answer: (b) Low precision What is False Positive (FP)?False positive is when the system (classifier) incorrectly classifies a wrong event as correct (positive) class. In other words, how many negative cases get incorrectly identified as positive. It is also referred as TYPE I error. Let us assume that we have developed a house alarm security system to automatically detect the presence of intruders. FALSE POSITIVE is, your alarm goes off when there is no intruder. Few other examples;
PRECISION is calculated as follows; Precision = TP / (TP + FP) If the system detects more FPs, it lowers the PRECISION of the underlying system. Hence, while building classification models, you may have to choose to build models with lower false positives if a high precision score is desirable as per your requirements.
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