(True/False) A large c term will penalize the SVM coefficients more heavily.1 pointTrueFalse

Analyzing the Statement

1. Understanding the term "c" in SVM: In Support Vector Machines (SVM), the parameter "C" is used as a regularization parameter that controls the trade-off between maximizing the margin and minimizing the classification error. A large value of "C" means that the SVM will prioritize minimizing classification errors more than maximizing the margin.

2. Impact of a large "C": A large "C" indeed means that the SVM is more sensitive to misclassifications because it will try to correctly classify all training data points, which can lead to overfitting. This implies that the model will allow less margin for the training examples, penalizing the coefficients less heavily, not more.

Conclusion

Thus, the statement "A large c term will penalize the SVM coefficients more heavily" is False. A larger "C" actually allows the model to fit the data more closely, reducing the penalty on misclassified points and allowing larger coefficients.