A.It represents the trade-off between underfitting and overfitting.

B.It is not relevant in machine learning.

C.It refers to the trade-off between the number of features and the model's complexity.

D.It indicates the trade-off between accuracy and precision.

A.Clustering Models

B.Decision Trees

C.Linear Regression

D.Principal Component Analysis (PCA)

A.Random Forest

B.Support Vector Machine (SVM)

C.K-Means Clustering

D.Linear Regression

A.Creating new words to improve model performance

B.Converting text to numbers for model input

C.Reducing words to their base or root form

D.Grouping similar words together based on their meanings

A.To test the model's generalization capability

B.To train the machine learning model

C.To validate the model's performance

D.To evaluate the model's predictions