Labeled example

An example that contains one or more features and a label. For example, the following table shows three labeled examples from a house valuation model, each with three features and one label:

Number of bedrooms	Number of bathrooms	House age	House price (label)
3	2	15	$345,000
2	1	72	$179,000
4	2	34	$392,000

In supervised machine learning, models train on labeled examples and make predictions on unlabeled examples

Self-training (machine learning) 이 글을 인용: “The ratio of unlabeled examples to labeled examples in the dataset is high.”
Log loss 이 글을 인용: “Since this is logistic regression, every value of must either be 0 or 1.”
Semi-supervised learning “Semi-supervised learning can be useful if labels are expensive to obtain but unlabeled examples are plentiful.”
ML crash course - Linear regression “In an ML context, linear regression finds the relationship between features and a label.”
Introduction to Machine Learning 관련 절: Definition of [[Machine learning|ML]]
역전파 “The difference between the prediction and the label value is the loss for that example.”
모델 (기계학습) “In supervised machine learning, a model takes an example as input and infers a prediction as output.”
Ground truth (machine learning) “Suppose the label is a floating-point value measured by instruments (for example, barometers).”
Epoch (machine learning) “A full training pass over the entire training set such that each example has been processed once.”
Machine Learning Systems “Machine Learning Systems provides a systematic framework for understanding and engineering machine learning (ML…”
Generalization (machine learning) “You train a model on the examples in the training set.”
Downsampling (machine learning) “For example, before training an image recognition model, downsampling high-resolution images to a lower-resolut…”
Sparse features “In machine learning, a surprising number of features are sparse features.”
Minority class (machine learning) “The less common label in aclass-imbalanced dataset.”
Iteration (machine learning) “A backward pass (backpropagation) to adjust the model's parameters based on the loss and the learning rate.”
기계학습 “2024-08-24 - What's Really Going On in Machine Learning?”
배치 크기 “For instance, if the training set contains a million examples, then the batch size would be a million examples.”
Interpretability (machine learning) “Most linear regression models, for example, are highly interpretable.”
선형 모델 “In contrast, the relationship of features to predictions in deep model is generally nonlinear.”
Parameter (machine learning) “For example, learning rate is a hyperparameter.”