16 Questions
What method is commonly used for variable selection in linear regression to prevent overfitting?
Elastic net
Which technique helps in identifying the most significant variables in a model by penalizing coefficients to zero?
Lasso regression
What is a common consequence of overfitting in predictive modeling?
Misleading correlation
Which model selection criterion penalizes additional complexity to prevent overfitting?
Akaike information criterion (AIC)
How does lasso regression differ from ridge regression in terms of variable selection?
Lasso regression encourages sparsity while ridge regression discourages it.
Which technique combines L1 and L2 penalties for variable selection and regularization?
Elastic net
Which R function is commonly used for making predictions from models?
predict
In predictive modeling, which R function is best suited for k-nearest-neighbor algorithm?
kknn
When building linear regression models in R, which function should be used?
lm
Which software package is most suitable for analyzing optimization models?
PuLP
Why might the selected model's expected performance when forecasting the next 36 months be worse than its observed performance on the validation data set?
The real situation may have changed, making the forecasted situation different from when the model was trained.
What common issue could arise if the selected model was chosen based on its performance on a validation set?
A biased model selection process leading to poor generalization.
What risk does overfitting present when using a predictive model for future forecasting?
Higher accuracy on the training data but potential poor performance on unseen data.
How does the potential presence of a selection bias affect the chosen model's forecasting capabilities?
Results in a better fit to random patterns in the validation data but may not generalize well.
How can changes in the real situation impact the performance of a predictive model over time?
Result in differences between forecasted situations and historical training/validation data.
What role does generalization play in evaluating a predictive model's performance for future forecasts?
It helps prevent overfitting by promoting simpler models that capture true patterns.
Test your knowledge on R functions for performing various analytics tasks. From cross-validation to support vector machines, this quiz will challenge you to match each analytics task with the correct R function.
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