PAML Week 4

What is the primary goal of Classification in Machine Learning?

• Predicting a continuous value

• Categorizing input into predefined classes or labels

• Grouping similar data points

• Minimizing the error between predicted and actual values

Which type of algorithm is suitable for predicting a continuous target variable based on one or more predictor variables?

• Classification algorithm

• Regression algorithm

• Clustering algorithm

• Reinforcement Learning algorithm

What is the key difference between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)?

• AI is a subset of ML, which is a subset of DL

• AI and ML are the same, while DL is a different concept

• DL is a subset of ML, which is a subset of AI

• AI and DL are the same, while ML is a different concept.

Which type of learning involves an agent learning from interactions with an environment to achieve a goal?

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Semi-Supervised Learning

What is the term for a model that performs well on the training data but fails to generalize to new, unseen data?

• Overfitting

• Underfitting

• Ideal-fitting

• Best-fitting

What is the main goal of Support Vector Regression (SVR)?

• Classifying data into categories

• Visualizing complex relationships in data

• Encoding categorical data

• Predicting continuous numeric values for non-linear relationships

What is K in K Nearest Neighbour (KNN)?

• The number of neighbours to include in the majority voting process

• The number of features in the dataset

• The number of classes in classification

• The distance metric used for prediction

Which machine learning task involves assigning multiple labels to a single input?

•  Multi-label Classification

• Regression

• Binary Classification

• Multi-Class Classification

What is the key characteristic of Simple Linear Regression?

• It uses multiple independent variables

• It predicts a numerical dependent variable using a single independent variable

• It is suitable for multi-class classification

• It predicts categorical variables

Why is it important to do data preprocessing?

• To enhance the visual aesthetics of the dataset accuracy and efficiency

• To reduce the computational complexity of the model

• To ensure the data is suitable for ML models which also increases the accuracy and efficiency.

• To introduce variability and complexity into the dataset