Quiz on Supervised Learning

Which of the following is a supervised learning algorithm?

• K-means clustering

• Decision tree

• Principal Component Analysis (PCA)

• Apriori algorithm

In supervised learning, the training dataset consists of:

• Input features only

• Output labels only

• Input features and output labels

• None of the above

Which supervised learning algorithm is known for its ability to handle both classification and regression tasks?

• Support Vector Machines (SVM)

• Random Forest

• K-nearest neighbors (KNN)

• Linear Regression

The main objective of a classification algorithm in supervised learning is to:

• Predict continuous values

• Determine the optimal number of clusters

• Assign input data to predefined categories or classes

• Identify patterns in unlabeled data

Which supervised learning algorithm is based on the concept of 'nearest neighbors'?

• K-means clustering

• Decision tree

• Naive Bayes

• K-nearest neighbors (KNN)

Which algorithm is used to minimize the errors between predicted and actual outputs in supervised learning?

• Decision tree

• Gradient Boosting

• K-means clustering

• Principal Component Analysis (PCA)

Which algorithm is prone to overfitting in supervised learning?

• Logistic Regression

• Support Vector Machines (SVM)

• K-means clustering

• Linear Regression

Which supervised learning algorithm is an ensemble method that combines multiple weak learners to make predictions?

• K-means clustering

• Random Forest

• Naive Bayes

• K-nearest neighbors (KNN)

The term 'supervised' in supervised learning refers to:

• The presence of a teacher or supervisor during the learning process

• The use of labeled data for training

• The requirement of human supervision for algorithm execution

• The need for a predefined set of rules for decision making

Which algorithm is suitable for handling multi-class classification problems in supervised learning?

• Linear Regression

• Decision tree

• Naive Bayes

• Multinomial Logistic Regression