Sentence examples for variables that fit from inspiring English sources

Exact(6)

They come up with illogical combinations of variables that fit the noise in the data rather than the signal and that are not robust to the difficulties in measuring the economy.

These unobserved concepts of consumer attitudes towards bioenergy/biofuels are based on the linear combination of 24 bioenergy statement variables that fit well in the PCA model (Table 2).

That is, if you know the end result you are aiming for in terms of raising your loved ones, then it will be much easier to not only spot the variables that fit into the equation of achieving that result, but also -- and maybe more importantly -- much easier to spot the ones that will definitely NOT fit into it.

The continuous variables that fit the Gaussian distribution were compared by using the independent samples t test, and the other parameters are compared by using the chi-square test.

The Health Belief Model was used as the theoretical framework for variable selection and modeling, particularly looking at variables that fit into the model's four main constructs of perceived susceptibility, severity, barriers and benefits [ 23].

As a consequence, it is common to select variables that fit nicely the training set and fail dramatically on independent validation sets, thus leading to unstable gene signatures (Ein-Dor et al., 2005; Michiels et al., 2005) and poor prediction models.

Similar(54)

It is possible to have a panel of calculated variables that fits more or less appropriately the intended goal.

It is applied to define the subset of variables that best fit the model.

The independent variables that best fit the final models were: age, self-reported health status, reason for health service use, improvement of health status after the consultation, waiting time, consultation length, payment of consultation, prescription filling and institution of care (Table 2).

Although the univariable P value for sire hearing status was <0.10, this variable was not included in multivariable modelling as sire status was unknown for 298 of the 810 study dogs, and because sire hearing status was probably causally associated with other exposure variables that were fitted.

I am wary of models that use more obscure variables or combinations of variables that happen to "fit" the past data better but that will produce overconfident forecasts when applied predicatively.

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