afunding and financing their activities is being shifted more and more on to the shoulders of the individual than the state 资助和财务他们的活动比状态被转移越来越到个体的肩膀 [translate] a(dimensionality reduced) dictionary Xi is over-complete (减少的幅员)字典XI是在完全的 [translate] ...
Dimensionality Reduced Robust Ordinal Regression applied to Life Cycle AssessmentLife Cycle AssessmentMulti-Criteria Decision AnalysisRobust Ordinal RegressionDimensionality ReductionPCAWEEELife Cycle Assessment quantifies the multi-dimensional impact of goods and services and can be handled by Multi-Criteria ...
X_reduced=pca.fit_transform(X) 另一个选择是以维数为自变量,可释方差(explained variance)为因变量,画出函数图形: 8.3.7 PCA用于压缩 在MNIST数据集应用PCA,保留95%的差异,仅需150个特征,远小于原始的784个特征,这是一个不错的压缩率。压缩之后还可以解压缩到784维,但这并不能得到原始数据,只是跟选择数据...
reduced dimensionality system 低维系统 dimensionality of array 【计】 数组维数 anatomical reduction 解剖复位 articulation reduction 清晰度降低 bacterial reduction 细菌还原作用 Clemmensen reduction 克莱门森还原 edge reduction 侧边压缩 相似单词 dimensionality 度数; 维数 Reduction n. 1.减少;缩小;降...
reduced to 1.(事、物)变成 2.(人)沦于 digestive system and respiratory system 消化系统和呼吸系统 reporting system; income declaration system 申报制度 suction pipe system with filter system 带滤水器的吸水管 相似单词 dimensionality 度数; 维数 system n. 1.系统 2.制度;体制 3.[the system...
reducedDimNames(sce.zeisel)#[1]"PCA"dim(reducedDim(sce.zeisel,"PCA"))#[1]281650reducedDim(sce.zeisel,"PCA")[1:10,1:6] 10个细胞的前6个主成分的指标 观察每个主成分的细胞异质性(方差解释)的捕获比例 代码语言:javascript 复制 percent.var<-attr(reducedDim(sce.zeisel),"percentVar")#[1]24.518...
reducedDimNames(sce.zeisel)#[1]"PCA"dim(reducedDim(sce.zeisel,"PCA"))#[1] 2816 50reducedDim(sce.zeisel,"PCA")[1:10,1:6] 10个细胞的前6个主成分的指标 观察每个主成分的细胞异质性(方差解释)的捕获比例 percent.var<-attr(reducedDim(sce.zeisel),"percentVar")# [1] 24.5181077 7.1739169 4.84...
reducedDimNames(sce.zeisel) #[1] "PCA" dim(reducedDim(sce.zeisel,"PCA")) #[1] 2816 50 reducedDim(sce.zeisel,"PCA")[1:10,1:6] 10个细胞的前6个主成分的指标 观察每个主成分的细胞异质性(方差解释)的捕获比例 percent.var <- attr(reducedDim(sce.zeisel),"percentVar") ...
Unlike selection, feature extraction is the transforming of existing data into less complex data that has a reduced number of variables. The goal here is to build derived values from the existing values, which may lead to a different but more relevant data set than the original data set. ...
Reduced storage space.It reduces storage space as the process eliminates irrelevant data. Feature extraction.Dimensionality reduction aids in extracting relevant features from high-dimensional data. Data compression.It compresses data, which improves its storage and processing efficiency. ...