Examples of using Dimensionality reduction in English and their translations into Chinese
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Dimensionality reduction is yet another common unsupervised learning task.
Dimensionality reduction is sometimes also used to visualize data.
有时，降维也被应用到数据可视化上。Could the steps performed above represent a dimensionality reduction method?
上述步骤可以表示降维方法吗？?PCA is one of the most often applied dimensionality reduction techniques.
PCA是最常用的线性降维技术之一。Unsupervised learning: density estimation, clustering, and dimensionality reduction methods.
无监督学习：密度估计，聚类和降维方法。Two common use-cases for unsupervised learning are exploratory analysis and dimensionality reduction.
无监督学习的两种常见用例是探索性分析和降维。Most big data visualization uses dimensionality reduction to identify trends and rules.
大多数大数据可视化使用降维来识别趋势和规则。Most big data visualization uses dimensionality reduction to identify trends and rules.
大多数数据可视化使用降维来识别趋势和规则。Gene- environment interactions were analyzed using the multifactor dimensionality reduction(MDR) method.
基因一环境因素之间的高阶交互作用采用多因子降维法(Multifactordimensionalityreduction，MDR)进行分析。Dimensionality Reduction: Process of reducing the number of random variables under consideration.
降维（Dimensionreduction）：减少需要考虑的变量数量。Deliver principled dimensionality reduction based on the data set's network model structure.
根据数据集的网络模型结构提供原则性降维.Like clustering methods, dimensionality reduction seeks an inherent structure in the data.
与聚类方法类似，降维算法寻找数据中的固有结构。From a mathematical point of view, this is a dimensionality reduction processing technique.
从数学角度来看，这是一种降维处理技术。Dimensionality Reduction: The process of reducing the number of features under consideration.
降维（Dimensionreduction）：减少需要考虑的变量数量。PCA can be used to do both of the dimensionality reduction styles discussed above.
PCA可用于执行上面讨论的两种降维方式。Dimensionality reduction has the goal of simplifying the data without losing too much information.
相关的任务是Dimensionalityreduction（降维），它的目标是在不丢失太多信息的情况下去简化数据。PCA can be used to do both of the dimensionality reduction styles discussed above.
PCA可以用于上面讨论的两种降维方式。PCA can be used to do both of the dimensionality reduction styles discussed above.
PCA可以用来进行上述两种降维方式的操作。The 1x1 convolutions(or network in network layer) provide a method of dimensionality reduction.
X1的卷积(或者网络层中的网络)，提供了一个减少维度的方法。This is useful for data dimensionality reduction and it could also be applied to KPCA.
这对于数据降维十分有用，而这一技巧也可以用在核PCA中。
