Sentence examples for a weight to each from inspiring English sources

The phrase "a weight to each" is not correct in standard written English.
It may be intended to convey the idea of assigning a specific weight or importance to each item or individual in a context, but it lacks clarity.
Example: "In our analysis, we assigned a weight to each factor to determine their overall impact on the results."
Alternatives: "an importance to each" or "a value to each".

Exact(60)

To address this and to improve the strain estimation, we adopt a weighted least-squares (WLS) method and assign a weight to each displacement measurement based on the known variance of that measurement.

According to Drobne and Lisec (2009) with the weighted linear combination, factors are combined by applying a weight to each followed by a summation of the results to yield a suitability map: S; = ;sum {w_{i} } x_{i} where, S is suitability, w i is weight of factor i, and x i is the criterion score of factor I (Drobne and Lisec 2009).

To sidestep this difficulty, an alternative approach combines weighted kernels with SVMs [19] [22]; this approach assigns a weight to each variable to indicate its relevance.

We formulate the problem as a multi-criteria optimization problem and attributing a weight to each criterion.

It provides a systematic approach to explore and analyze influential relationships between agile-enabling factors and assigns a weight to each factor representing its relative importance.

Moreover, we will introduce a novel procedure of weighting ensemble components, i.e. decision trees, by assigning a weight to each leaf of the tree.

ICM has long afforded a weight to each age bracket 18-244, 25-34 and so on) to match the group's size in the census but is now concerned that the individual respondents in each bracket may not be representative of that group.

Specifically, we first present an evaluation criterion named multiclass kernel polarization (MKP) to assess the quality of a kernel in the multiclass classification scenario, and then develop a heuristic rule to directly assign a weight to each kernel based on the quality of the individual kernel.

LQSR assigns a weight to each link.

Their non-parametric estimate involves assigning a weight to each subject.

Robust regression works by assigning a weight to each data point.

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