2016年4月1日 · Basically a class label (in classification) can be compared to a response variable (in regression): a value we want to predict in terms of other (independent) variables. Difference is that a class labels is usually a discrete/Categorcial variable (eg-Yes-No, 0-1, etc.), whereas a response variable is normally a continuous/real-number variable.

1）比如推理得到class序号是980，需要先在imagenet_classes.txt中找到第981个class（因为索引从0开始，所以是第981个类别，但在下面imagenet_classes 中查索引还是按照980查找）是 n09472597，然后再在imagenet_synsets.txt 中找这个序号对应的含义，是volcano，所以推理结果 …

2022年6月9日 · Mnemonic : A label is a category that allows us to differentiate (label) our data. A multi-class multi-label classification is a classification with more than two classes and more than one label. Note that different labels for data do not necessarily imply the same classes.

2023年3月23日 · 在监督学习中利用数据做训练时，有标签数据/样本（Labeled data）或叫有/无标记数据，就是指有没有将数据归为要预测的类别。 包含特征，但不包含标签. 在使用有标签样本训练模型之后，我们会使用该模型预测无标签样本的标签。 在垃圾邮件检测器示例中，无标签样本是用户尚未添加标签的新电子邮件。 模型定义了特征与标签之间的关系，就是我们机器学习的一组数据关系表示，也是我们学习机器学习的核心. 例如，垃圾邮件检测模型可能会将某些特征与“垃 …

2020年8月19日 · Classification is a task that requires the use of machine learning algorithms that learn how to assign a class label to examples from the problem domain. An easy to understand example is classifying emails as “ spam ” or “ not spam.”

对 class_labels 进行 embedding 获取到 class_emb （class_emb可以为空） 通过 emb = t_emb + class_emb 获取到最终嵌入变量 emb 也是后边 temb 输入的参数; 对 sample 进行一次卷积得到 sample; 遍历下采样模块，依次执行（每次的输出保存到 res_samples） 执行中间层模块

2023年5月6日 · Classification is a task in data mining that involves assigning a class label to each instance in a dataset based on its features. The goal of classification is to build a model that accurately predicts the class labels of new instances based on their features.

2024年8月8日 · Classification is a supervised machine learning method where the model tries to predict the correct label of a given input data. In classification, the model is fully trained using the training data, and then it is evaluated on test data before being used to …

2022年8月15日 · In machine learning, a class label is a categorical variable that is used to indicate which class an instance belongs to. The class label can be used to improve the efficiency of machine learning algorithms by reducing the amount of data that needs to be processed.

2025年2月17日 · Partial-label learning (PLL) is a weakly supervised learning paradigm that allows training classifiers in this context without manual data cleaning. While state-of-the-art methods have good predictive performance, their predictions are sensitive to high noise levels, out-of-distribution data, and adversarial perturbations.