in number of variables vs in the number of variables

Both phrases are correct, but they are used in different contexts. 'In number of variables' is used when discussing quantities or comparisons, while 'in the number of variables' is used when referring to a specific count of variables. The choice between the two depends on the context in which they are used.

Last updated: March 17, 2024 • 714 views

in number of variables

This phrase is correct and commonly used when discussing quantities or comparisons.

This phrase is used when referring to quantities or comparisons of variables without specifying a specific count.

Examples:

The complexity of the algorithm increases in number of variables.
There is a significant difference in number of variables between the two datasets.

Show examples from the web [+]

Sep 26, 2005 ... Probabilistic inference example. Flu. Allergy. Sinus. Headache. Nose=t. Inference seems exponential in number of variables!
exponential in number of variables co-mentioned with that variable. •Without variable elimination, exponential in number of summation variables. Overview.
error rate (or MSE) at each step down in number of variables. 5. Steps 1-4 are repeated 10-50 times to smooth out the variability; select p that minimizes the ...
reduction in number of variables that may reach 3-6% of the original numbers. Such reduction leads to significant reduction in the complexity of the model and ...

Alternatives:

with the number of variables
among the variables
regarding the variables
related to the variables
concerning the variables

in the number of variables

This phrase is correct and commonly used when referring to a specific count of variables.

This phrase is used when specifying a particular number of variables being discussed.

Examples:

The error rate increases in the number of variables from three to five.
There is a difference in the number of variables used in the two experiments.

Show examples from the web [+]

The change in the number of variables from 200 to 500 causes the Forward Stepwise MSE to increase and implies a breakdown point at lower sparsity levels .
The change in the number of variables from 200 to 500 causes the Forward Stepwise. MSE to increase and implies a breakdown point at lower sparsity levels.
Feb 17, 2012 ... Most clustering algorithms just use distance functions, and these usually are linear in the number of variables. However, not every result will be ...
Feb 18, 2013 ... "I could construct an algorithm that scales polynomially in the number of constraints or variables but not in the number of variables and ...

Alternatives:

within the number of variables
inside the number of variables
amidst the variables
amid the variables
inside the variables

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in number of variables vs in the number of variables