Overfitting occurs when a model performs well on training data but poorly on unseen data.Group of answer choicesTrueFalse

Dropout increases the model’s training error but decreases the test error, preventing overfitting.Group of answer choicesTrueFalse

Overfitting occurs when a model:Question 7AnswerA.Has high bias and low varianceB.Has low bias and high varianceC. Performs well on unseen dataD. Fails to capture the underlying patterns in the data

The use of dropout in a neural network can help reduce the risk of overfitting.Group of answer choicesTrueFalse

Question 3What is overfitting in machine learning?a) Overfitting occurs when a model has high complexity and captures both information and noise in the training data.b) Overfitting occurs when a model has poor performance on the training data.c) Overfitting is indicated when a model has good performance on the training dataset but relatively poor performance on the testing dataset.d) Overfitting occurs when a model has good performance on the test data.Answer choicesSelect only one optionREVISITa onlya & da & ca, c & d

A machine learning model is trained to predict customer churn for a telecom company. The model achieves high accuracy during training but performs poorly when applied to new, unseen data. What could be the most likely cause of this issue?a)Inappropriate choice of evaluation metricb)Insufficient training datac)Underfittingd)Overfitting