Sentence examples for irrelevant variables from inspiring English sources

The cost of adding one or more irrelevant variables is loss of efficiency...

This paper explores this issue using an econometric modeling approach, considering irrelevant variables, multicollinearity, omitted variable bias, and endogeneity bias.

By combining the removal of irrelevant variables with this new characterization of weak cause, we then obtain techniques for deciding and computing causes and explanations in the structural-model approach, which can be done in polynomial time under suitable restrictions.

An explanation based on few samples (often even a singleton sample) from these irrelevant variables is typically almost as good as an explanation based on (the computationally costly) marginalization over these variables.

However, three major problems usually appear using the ELM structure: (i) the dataset may have irrelevant variables, (ii) choosing the number of neurons in the hidden layer would be difficult, and (iii) it may encounter the singularity problem.

To this end, we first explore how an instance of deciding weak cause can be reduced to an equivalent instance in which irrelevant variables in the (potential) weak cause and the causal model are removed, which extends previous work by Hopkins.

To decrease the negative influence of the auto-correlated and irrelevant variables, a key variable identification procedure using recursive feature elimination, based on the SVM is implemented, with time lags incorporated, before every classifier is trained, and the number of relatively important variables to every classifier is basically determined by 10-fold cross-validation.

Decision trees also have the ability to discard irrelevant variables.

The effect of "irrelevant" variables on decision making: Criterion shifts in preferential choice?

For completeness, we additionally verified sensitivity to the irrelevant mean and variance via this approach, making separate plots for UVr and UMr (correlations with the task-relevant variables) and UVi and UMi (correlations with the task-irrelevant variables; see also Fig. 2 b).

For this reason, it is important that any experiment in which Fos expression is used as a means of identifying the neural structures involved in particular behavioural processes should employ a control procedure that is matched as closely as possible to the index task on these 'irrelevant' variables.