Exploring Machine Learning Concepts

What is the main goal of supervised learning?

• To reduce the amount of data used for training.

• To classify data without any labels.

• To create unsupervised models for clustering.

• To train a model to make predictions based on labeled data.

Which of the following is a common application of unsupervised learning?

• Sentiment analysis

• Image classification

• Customer segmentation

• Spam detection

In reinforcement learning, what is the role of the agent?

• The agent's role is to only learn from past experiences without making decisions.

• The agent's role is to passively receive rewards without influencing outcomes.

• The agent's role is to make decisions and take actions to maximize cumulative rewards in an environment.

• The agent's role is to observe the environment without taking any actions.

What does a Support Vector Machine (SVM) primarily do?

• A Support Vector Machine (SVM) generates random data points for analysis.

• A Support Vector Machine (SVM) is used for clustering similar data points together.

• A Support Vector Machine (SVM) primarily classifies data by finding the optimal hyperplane that separates different classes.

• A Support Vector Machine (SVM) primarily predicts future values based on historical data.

How does semi-supervised learning differ from supervised learning?

• Semi-supervised learning uses both labeled and unlabeled data, while supervised learning uses only labeled data.

• Semi-supervised learning requires more labeled data than supervised learning.

• Semi-supervised learning is only applicable to small datasets.

• Supervised learning can use both labeled and unlabeled data.

What type of data is used in supervised learning?

• Unstructured data

• Unlabeled data

• Structured data

• Labeled data

Can unsupervised learning be used for classification tasks? Why or why not?

• Unsupervised learning is primarily used for supervised classification tasks.

• Yes, unsupervised learning can classify data into predefined categories.

• Unsupervised learning can be used to label data directly without any prior information.

• No, unsupervised learning cannot be used for direct classification tasks.

What is the purpose of the reward signal in reinforcement learning?

• The reward signal indicates the success of an agent's actions in achieving its goals.

• The reward signal is used to track the agent's location.

• The reward signal determines the agent's learning rate.

• The reward signal punishes the agent for poor decisions.

What is a kernel in the context of Support Vector Machines?

• A kernel is a function that transforms input data into a higher-dimensional space for better separation of classes in SVM.

• A kernel is a data preprocessing technique that normalizes input features.

• A kernel is a type of machine learning algorithm used for classification.

• A kernel is a graphical representation of the SVM model.

What are some common algorithms used in unsupervised learning?

• Linear regression

• Support vector machines

• Decision trees

• K-means, hierarchical clustering, PCA, t-SNE, Apriori