supervised learning
英 [ˈsuːpəvaɪzd ˈlɜːnɪŋ]
美 [ˈsuːpərvaɪzd ˈlɜːrnɪŋ]
网络 有监督学习; 监督式学习; 有导师学习; 有指导的学习; 有监督的学习
双语例句
- Supervised learning is tasked with learning a function from labeled training data in order to predict the value of any valid input.
监管学习的任务是学习带标签的训练数据的功能，以便预测任何有效输入的值。 - Common examples of supervised learning include classifying e-mail messages as spam, labeling Web pages according to their genre, and recognizing handwriting.
监管学习的常见例子包括将电子邮件消息分类为垃圾邮件，根据类别标记网页，以及识别手写输入。 - A decade ago, it was thought that supervised learning was the way to do this: A team of linguists created dictionaries and grammar rules and taught them to the computer.
十年前，人们认为监督式学习是实现它的方法：一组语言学家造出字典，语法规则，然后，把它们教给计算机。 - Decomposition of SAR images 'mixed pixels based on supervised learning ICA algorithm
基于SL-ICA算法的SAR图像混合像元分解 - An 3D Expression Generating Method Based on Morphing and Supervised Learning
一种基于变形和监督式学习的三维表情生成方法 - In order to develop linear local tangent space alignment to supervised learning algorithm, an algorithm called orthogonal discriminant linear local tangent space alignment is proposed.
为了将线性局部切空间排列算法发展为有监督的学习算法，提出了一种正交判别的线性局部切空间排列算法。 - This paper proposes a method combining supervised learning with unsupervised method to conduct CWS, which incorporates unsupervised segmentation into Conditional Random Fields ( CRFs).
该文提出一个基于条件随机场（CRF）的古汉语自动断句标点方法，并引入互信息和t测-试差两个统计量作为模型的特征。 - Supervised learning with the use of regression and classification networks with sparse data sets will be explored.
也将在课程中以带有稀疏值理论的分类神经网路与回归的使用来探讨监督式学习。 - After supervised learning, the visual network can extract image features and classify patterns.
经过学习的视觉模式识别网络，可完成图像特征的提取，实现相对于图像平移和尺度不变的模式识别。 - A new hybrid supervised learning control scheme is presented for continuous stirred tank reactor ( CSTR) systems.
提出了一种连续搅拌反应釜（CSTR）的混合监督学习控制方法。 - The system adopts supervised learning, Naive Bayes as the categorization model and information gain as the feature selection.
系统采用有指导的学习方法，选取NaiveBayes作分类模型和信息增益作为特征提取方法。 - Unsupervised learning is used to adjust input weight values and supervised learning is utilized to adjust output weight values.
学习过程中，采用无监督学习算法对输入权重进行调整，采用有监督学习算法对输出权重进行调整。 - A series of formulation and a supervised learning algorithm of multi-views subspace analysis were investigated and obtained.
给出了ISA视角子空间分析公式和有效的多视角子空间有监督学习算法。 - Lattice machine is a novel approach to supervised learning.
格机是一种新颖的有监督学习方法。 - A supervised learning evidence theory classifier is proposed to solve this problem.
通过在证据理论中引入神经网络的学习机制，该文提出了一种有监督学习证据理论分类器。 - Other feedforward models and supervised learning models.
其它前馈型网络模型和监督学习模型； - In Multi-Agent Systems, supervised learning algorithms are widely used such as the Artificial Neuron Network and Decision Tree.
其中，有施教者的学习算法在多Agent系统中应用最为普遍，比如人工神经网络算法和决策树算法等。 - At present, text categorization based on supervised learning is a mature technology to solve the problem.
目前，解决此问题较为成熟的技术是有监督的文本分类技术。 - Compared with traditional supervised learning and unsupervised learning, semi-supervised learning is in a rather new field.
目前在机器学习界，主要还是传统的监督学习和非监督学习两大类别，半监督学习还属于一个比较新颖的领域。 - Compared to supervised learning, unsupervised learning of a late start has greater space for its research.
相对于有监督学习来说，非监督学习的研究起步较晚，其研究空间比前者更大。 - DSPE is a linear supervised learning method which can extract features effectively and has good robustness.
该方法是一个线性的监督算法，能够有效地提取特征，具有较高的鲁棒性。 - In this thesis, first of all, the importance of supervised learning for feature extraction is discussed.
本文首先讨论了监督学习在特征提取上的重要性。 - Propose a new ensemble supervised learning algorithm following by feature selection that is suitable for high dimensional data.
提出了一种新的适于高维数据的有监督的特征选择集成学习算法。 - And raises a combined method which combines supervised learning method and semi-supervised learning method to drug name recognition.
本文提出了一种监督学习和半监督学习相结合的方法进行命名实体识别。 - Different kinds of Gaussian process classification methods compared with the traditional supervised learning.
同时，还对不同种高斯过程分类方法与三种经典的监督式学习方法进行分类检测对比实验。 - Meanwhile covering algorithm is a supervised learning algorithm, which requires a lot of labeled examples.
同时覆盖算法是一个监督学习，需要大量的有标记数据。 - Because of using the known model to predict new data, Classification is a favourable supervised learning process.
由于分类是利用已知的模型对新的数据进行预测，因此它是一个很好的有监督的学习过程。 - Comparing with the supervised learning, it saves the cost of tagging samples.
相比较于监督学习算法，它节省了标注样本所需要的大量成本，相比较于无监督来说，它保证了准确度。 - Semi-supervised learning flourishes as it can circumvent the limitations of unsupervised learning and supervised learning.
半监督学习的蓬勃发展规避了无监督学习和监督学习的局限性。 - Constrained clustering and transductive learning mainly deal with learning problems between unsupervised learning and supervised learning.
约束聚类和约束分类主要处理学习问题的方式间于无监督学习和监督学习。