목차 목차 관련 글 Downsampling (machine learning) 이 글을 인용: “For example, in a class-imbalanced dataset, models tend to learn a lot about the majority class and not enough …” Recall (machine learning) “False negative means that the model mistakenly predicted the negative class.” ML crash course - Classification “When the total of actual positives is not close to the total of actual negatives, the dataset is imbalanced.” Precision (machine learning) “When the model predicted the positive class, what percentage of the predictions were correct?” Positive class (machine learning) “For example, the positive class in a cancer model might be "tumor."” Accuracy (machine learning) 관련 절: When to use 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.” 분류 모델 “A model that predicts the positive or negative class for a particular medical condition.” Machine Learning Systems “Machine Learning Systems provides a systematic framework for understanding and engineering machine learning (ML…” Negative class (machine learning) “In binary classification, one class is termed positive and the other is termed negative.” Class (machine learning) “In contrast, a regression model predicts a number rather than a class.” Classification threshold “If this raw value is less than the classification threshold, then the negative class is predicted.” Self-training (machine learning) “Use the model created in Step 1 to generate predictions (labels) on the unlabeled examples, moving those in whi…” 지도 학습 “Supervised machine learning is analogous to learning a subject by studying a set of questions and their corresp…” Epoch (machine learning) 주제어가 겹침 Example (machine learning) “Examples in supervised learning fall into two general categories:” Iteration (machine learning) 주제어가 겹침 Generalization (machine learning) 주제어가 겹침 모델 (기계학습) “Unsupervised machine learning also generates models, typically a function that can map an input example to the …” 기계학습 “2024-08-24 - What's Really Going On in Machine Learning?”