Lecture 10 Flashcards
What is classification in machine learning?
A task that assigns a class label to a data point based on its features.
What is the difference between binary and multiclass classification?
Binary classification has two possible classes, while multiclass classification has more than two.
What is a probabilistic classifier?
A classifier that assigns probabilities to each possible class and selects the one with the highest probability.
What is the Naive Bayes classifier based on?
Bayes’ theorem and the assumption that all features are conditionally independent given the class.
Why is the Naive Bayes classifier considered naive?
Because it assumes all features are conditionally independent, which is often not true.
What is an example of a feature in classification?
A student’s attendance in lectures when predicting if they will pass a course.
How does the Naive Bayes classifier calculate class probabilities?
By multiplying prior probabilities with conditional probabilities of each feature given the class.
What is the purpose of smoothing in Naive Bayes?
To prevent zero probabilities by adding a small value to all probability estimates.
What is k-Nearest Neighbour (k-NN)?
A classification algorithm that assigns a class based on the majority class of the k closest data points.
How does k-Nearest Neighbour measure similarity?
Using distance metrics such as Euclidean distance between feature vectors.
What is the main limitation of the k-NN algorithm?
It is sensitive to noise and computationally expensive for large datasets.
What is the difference between supervised and unsupervised learning?
Supervised learning uses labeled data, while unsupervised learning finds patterns in unlabeled data.
What is semi-supervised learning?
A learning approach that uses a mix of labeled and unlabeled data.
What is reinforcement learning?
A learning method where an agent interacts with an environment and learns by receiving rewards and penalties.
What is regression in machine learning?
A supervised learning task that predicts a continuous numerical value instead of a class label.
What is an example of a regression problem?
Predicting stock market prices based on historical data.
What is ranking in machine learning?
A supervised learning task that orders items based on a criterion, such as search engine results.
What is collaborative filtering?
A technique used in recommender systems to suggest items based on user preferences and similar users.
What is clustering in machine learning?
An unsupervised learning task that groups similar data points together.
What is an example of clustering?
Grouping similar images in an image dataset.
How is deep learning related to machine learning?
Deep learning is a subset of machine learning that uses neural networks to model complex patterns.
What is an adaptive intelligent agent?
An AI system that learns from interactions with its environment and improves over time.
What is the difference between AI and machine learning?
AI is a broader field that includes machine learning, reasoning, and planning, while machine learning focuses on learning from data.
What is a supervised learning problem?
A problem where a model learns from labeled examples, such as spam detection.
What is the purpose of machine learning in AI?
To approximate answers and make predictions using data-driven models.
