Sentence examples for are principal components from inspiring English sources

The phrase "are principal components" is correct and usable in written English.
It can be used in contexts related to statistics, data analysis, or machine learning, particularly when discussing the results of principal component analysis.
Example: "In our study, the first two factors identified are principal components that explain the majority of the variance in the dataset."
Alternatives: "constitute principal components" or "represent principal components".

Exact(13)

In addition to government employment, services and tourism are principal components of the city's economy.

Intermediate filaments (IFs) are principal components of the cytoskeleton, a dynamic integrated system of structural proteins that provides the functional architecture of metazoan cells.

The RNA-binding proteins, TDP-43 and FUS, are principal components of cytoplasmic inclusions found in motor neurons of ALS patients and mutations in TDP-43 and FUS are linked to familial and sporadic ALS.

State-of-the-art in this context are principal components transform [2, 18] combining multiple normalised iris textures at image-level obtained by different segmentation algorithms.

The eigenvectors of the correlation matrix are principal components and each original observation is converted to principal component score by projecting it onto the principal axes (Chen et al. 2007).

Adherens junctions (AJs) and tight junctions (TJs) are principal components of cell-cell junctions that control the paracellular transport of other cells and proteins, and ultimately maintain normal barrier function.

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Similar(47)

These are principal component analysis (PCA) and cluster analysis (CA).

They are Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Non-negative Matrix Factor (NMF).

Methods used are: Principal Component Analysis, Factor Analysis and Cluster Analysis.

Among them are principal component analysis [ 4] and independent component analysis [ 5].

Typical workhorses to explore this are Principal Component Analysis (pca) and Hierarchical Cluster Analysis (hca).

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