使用labeled data和unlabeled data的关联结构来提高分类精度。我们可以假设,一个example的预测标签将要被它相关的example的预测标签所影响。 5另外一个想法 Using Weighted Nearest Neighbor to Benefit from Unlabeled Data 使用labeled data来进行训练分类器。使用这个分类器对unlabeled data进行分类,给出相应的信任权重。我...
Semi-supervised learning typically is a learning task from both labeled and unlabeled data. We especially consider the multiclass semi-supervised classification problem. To solve the multiclass semi-supervised classification problem we propose a new multiclass loss function using new codewords. In the...
Combining_labeled_and_unlabeled_data_with_co-training 下载积分: 3000 内容提示: Combining Lab eled and Unlab eled Data with Co-Training? yAvrim BlumScho ol of Computer ScienceCarnegie Mellon UniversityPittsburgh, PA 15213-3891avrim+@cs.cmu.eduTom MitchellScho ol of Computer ScienceCarnegie Mellon...
Due to the considerable time and expense required in labeling data, a challenge is to propose learning algorithms that can learn from a small amount of labeled data and a much larger amount of unlabeled data. In this paper, we propose one such algorithm which uses an evolutionary strategy to...
Labeled Data Explained While unlabeled data consists of raw inputs with no designated outcome, labeled data is precisely the opposite. Labeled data is carefully annotated with meaningful tags, or labels, that classify the data's elements or outcomes. For example, in a dataset of emails, each em...
Speci cally, the presence of two distinct views of each example suggests strategies in which two learning algorithms are trained separately on each view, and then each algorithm's predictions on new unlabeled examples are used to enlarge the training set of the other. Our goal in this paper ...
example x x such that f x f x useful We explore a generalization of this idea in Sec Whymightwe expect unlabeleddatatobe useful for tion where we show that any weak hypothesis can amplifying a small labeled sample in this context We be boosted from unlabeled data if D has such a...
Data is the reason AV companies are racking up miles and miles of testing experience on public roads, recording and stockpiling petabytes of road lore. Waymo, for example, claimed in July more than 10 million miles in the real world and 10 billion miles in simulation. ...
f0; 1gn and C1 = C2 = \conjunctions over f0; 1gn." Say that it is known that the rst coordinate is relevant to the target concept f1 (i.e., if the rst coordinate of x1 is 0, then f1 (x1 ) = 0 since f1 is a conjunction). Then, any unlabeled example (x1 ; x2) such ...
Zhu X. and Ghahramani Z. Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, 2002. 概 本文通过将有标签数据传播给无标签数据