Machine Learning Fundamentals Flashcards
6 cards from real Artificial Intelligence practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Machine Learning Fundamentals flashcards as text
What is the role of a hyperparameter in machine learning?
Answer: A configuration set before training that controls model behavior
Hyperparameters are set prior to training and control aspects of the learning process, such as learning rate or tree depth.
Which ensemble method trains models sequentially, with each new model correcting the errors of the previous one?
Answer: Boosting
Boosting sequentially trains weak learners, each focusing on the mistakes of its predecessor to build a strong combined model.
What does AUC-ROC measure in a binary classification model?
Answer: The model's ability to distinguish between classes across all classification thresholds
AUC-ROC summarizes the ROC curve into a single value representing the model's overall ability to discriminate between positive and negative classes.
Which technique reduces the number of features while preserving as much variance as possible?
Answer: Principal Component Analysis (PCA)
PCA transforms data into a lower-dimensional space by projecting onto the axes of greatest variance (principal components).
What is a confusion matrix used for in classification tasks?
Answer: Summarizing the counts of correct and incorrect predictions by class
A confusion matrix shows the true positives, false positives, true negatives, and false negatives for each class, giving a detailed view of classifier performance.
What is 'data leakage' in a machine learning pipeline?
Answer: When test set information unintentionally influences model training
Data leakage occurs when information from outside the training set is used to build the model, leading to overly optimistic evaluation metrics.