In binary classification , the class you are testing for. For example, the positive class in a cancer model might be “tumor.” The positive class in an email classifier might be “spam.”1
The term positive class can be confusing because the “positive” outcome of many tests is often an undesirable result. For example, the positive class in many medical tests corresponds to tumors or diseases. In general, you want a doctor to tell you, “Congratulations! Your test results were negative.” Regardless, the positive class is the event that the test is seeking to find.1
Admittedly, you’re simultaneously testing for both the positive and negative classes.1
목차 목차 관련 글 Recall (machine learning) 이 글을 인용: “When ground truth was the positive class, what percentage of predictions did the model correctly identify as th…” Classification threshold 이 글을 인용: “In a binary classification, a number between 0 and 1 that converts the raw output of a logistic regression mode…” Precision (machine learning) 이 글을 인용: “When the model predicted the positive class, what percentage of the predictions were correct?” ML crash course - Classification “False positive (FP): A not-spam email misclassified as spam.” Area under the ROC curve 이 글을 인용: “A number between 0.0 and 1.0 representing a binary classification model's ability to separate positive classes …” Accuracy (machine learning) “False positive rate (a.k.a. probability of false alarm)” 로지스틱 회귀 이 글을 인용: “If the predicted number is greater than the classification threshold, the binary classification model predicts …” 분류 모델 “A model that predicts the positive or negative class for a particular medical condition.” False positive rate 이 글을 인용: “The proportion of actual negative examples for which the model mistakenly predicted the positive class.” Minority class (machine learning) “For example, given a dataset containing 99% negative labels and 1% positive labels, the positive labels are the…” Introduction to Machine Learning “Machine learning crash course: If you're ready for an in-depth and hands-on approach to learning more about ML.” Class (machine learning) “In a multi-class classification model that identifies dog breeds, the classes might be poodle, beagle, pug, and…” Downsampling (machine learning) “For example, in a class-imbalanced dataset, models tend to learn a lot about the majority class and not enough …” 참양성 이 글을 인용: “An example in which the model correctly predicts the positive class.” ROC curve “The shape of an ROC curve suggests a binary classification model's ability to separate positive classes from ne…” False positive 이 글을 인용: “An example in which the model mistakenly predicts the positive class.” Machine Learning Systems “Machine Learning Systems provides a systematic framework for understanding and engineering machine learning (ML…” Prediction (machine learning) “The prediction of a binary classification model is either the positive class or the negative class.” Majority class (machine learning) “For example, given a dataset containing 99% negative labels and 1% positive labels, the negative labels are the…” Epoch (machine learning) “In many cases, you'll need to experiment with how many epochs it takes for the model to converge.”