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unsupervised learning

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1. method in computing where systems find patterns in data without examples 2. process of gaining... See more

Vertaling van "unsupervised learning" in Chinees

Definitie

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无监督学习

非监督式学习

无监督式学习

This would be an example of unsupervised learning in a classification context.

这将在后面成为无监督学习上下文分类的一个例子。

The former belongs to supervised learning and the latter belongs to unsupervised learning.

它们分属于有监督学习与无监督学习。

Hebbian learning is considered to be a 'typical' unsupervised learning rule and its later variants were early models for long term potentiation.

赫布型学习被认为是一种典型的非监督式学习 规则，它后来的变种是长期增强作用的早期模型。

LDA is a supervised learning algorithm that utilizes the labels of the data, while PCA is an unsupervised learning algorithm that ignores the labels.

线性判别分析是一个监督式学习算法，会使用资料中的标签。而主成分分析是一个不考虑标签的非监督式学习 算法。

By analogy, ensemble techniques have been used also in unsupervised learning scenarios, for example in consensus clustering or in anomaly detection.

通过类比，集成技术也已用于无监督学习场景中，如共识聚类或异常检测。

This week, learn about unsupervised learning algorithms and how they can be applied to clustering and dimensionality reduction problems.

本周，我们学习无监督学习算法，以及这些算法如何应用于聚类和降维问题。

Unlike supervised learning, with unsupervised learning algorithms have no labels to learn from.

和监督式学习不同，无监督学习算法不需要学习标签。

k -means clustering has been used as a feature learning (or dictionary learning) step, in either (semi-)supervised learning or unsupervised learning. The basic approach is first to train a k -means clustering representation, using the input training data (which need not be labelled).

在（半）监督学习或无监督学习中，k -均值聚类被用来进行特征学习（或字典学习）步骤［18 ］。基本方法是，首先使用输入数据训练出一个k -均值聚类表示，然后把任意的输入数据投射到这一新的特征空间。

In the future, more sophisticated types of AI will use unsupervised learning.

将来，更精密类型的人工智能将采用无监督学习。

The differences between supervised and unsupervised learning Examples of where AI is being applied

监督学习与无监督学习的区别人工智能应用领域的实例

Transfer and unsupervised learning Re-ID

迁移和无监督学习的再识别

Detect topological phase transition in SSH model by unsupervised learning

在SSH模型里通过无监督学习检测拓扑相变

One is Jürgen Schmidhuber's multi-level hierarchy of networks (1992) pre-trained one level at a time through unsupervised learning, fine-tuned through backpropagation.

于尔根·施密德胡伯（英语：Jürgen Schmidhuber）于1992年提出多层级网络，利用无监督学习训练深度神经网络的每一层，再使用反向传播算法进行调优。