intercolline Antonyms
No Synonyms and anytonyms found
Meaning of intercolline
Webster
intercolline (a.)
Situated between hills; -- applied especially to valleys lying between volcanic cones.
intercolline Sentence Examples
- The intercollinearity between the independent variables created challenges in estimating the regression model.
- The presence of intercollinearity among the predictors rendered the interpretation of individual parameter estimates difficult.
- The variable selection process identified and removed highly intercolline variables to mitigate the impact on model stability.
- Transformational methods, such as centering and scaling, were employed to reduce the intercollinearity between the variables.
- Ridge regression was utilized as a robust technique to handle intercollinearity, preventing excessive parameter variance.
- The intercollinearity diagnosis highlighted the presence of redundant information within the dataset, leading to model overfitting.
- Partial least squares (PLS) regression was considered as an alternative approach to address intercollinearity, extracting latent variables that captured the most common variance.
- Regularization techniques, such as LASSO and elastic net, were employed to shrink the coefficients of highly intercolline variables, reducing their influence on the model.
- The research team conducted a thorough intercollinearity analysis to ensure the reliability and validity of their regression results.
- Machine learning algorithms, such as decision trees and random forests, are often more robust to intercollinearity compared to traditional regression models.
FAQs About the word intercolline
Situated between hills; -- applied especially to valleys lying between volcanic cones.
No synonyms found.
No antonyms found.
The intercollinearity between the independent variables created challenges in estimating the regression model.
The presence of intercollinearity among the predictors rendered the interpretation of individual parameter estimates difficult.
The variable selection process identified and removed highly intercolline variables to mitigate the impact on model stability.
Transformational methods, such as centering and scaling, were employed to reduce the intercollinearity between the variables.
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