Machine Learning Question

Error Jval () Jerain() m (Training Set Size) You train a learning algorithm, and find that it has unacceptably high error on the validation set. You plot the learning curve, and obtain the figure above. Is the algorithm suffering from high bias, high variance, or neither? A) High bias B) High Variance C) Neither f) Suppose you have implemented regularized logistic regression to classify what an object is in an image (i.e., to do object recognition). However, when you test your model on a new set of images, you find that it makes unacceptably large errors with its predictions on the new images. However, your model performs well (low error) on the training set. Which of the following steps are promising to take? 1. II. III. IV. Get more training samples. Try using a smaller set of features. Use fewer training samples. Try adding polynomial features. A) I, II, IV B) I and II C) I and IV D) only III E) only IV