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This is because we distinguish between the sample space of data from that of the minimal sufficient statistics.
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The between-cluster distances in the sample space is defined by (2) δ (X +, X − ) = d (∑ x + ∈ X + x + l +, ∑ x − ∈ X − x − l − ) where X + and X − are the positive and negative classes, respectively, and l + and l − are sample sizes of X + and X −, respectively.
PCA was performed in the sample space.
During the process of the first iteration, in the n-dimensional sample space, the distance between any two of negative samples is calculated.
Due to the tight linkage between the additional markers, SimWalk2 had difficulties accurately sampling from the entire sample space.
The first views gene selection and sample clustering as basically independent processes, the second dynamically uses the relationship between gene and sample spaces to iteratively apply a clustering and selection engine, while the third tries to cluster both genes and samples at the same time in a reduced space.
S B is the between-class scatter matrix in original sample space {mathbf{S}}_B={displaystyle sum_{i=1}^Cfrac{N_i}{N}left({overline{mathbf{x}}}_i-overline{mathbf{x}}right){left({overline{mathbf{x}}}_i-overline{mathbf{x}}right)}^T} (4).
Some interesting differences between the samples solidified in space and their counterparts solidified on the ground are described.
Feedback was provided in the form of a green "correct" or red "incorrect" in text in the space between the sample and matches at about the center of the projected screen.
Geometrically, (26) describes the distance between h ⌣ and h in the (L + 1 -dimensional sample space.
Many differences were found between the space samples and the ground samples.
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