ML WORKSHOP II CSE H

Among the following option identify the one which is not a type of learning

• Semi Unsupervised Learning
• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning

Answer explanation

Semi Unsupervised Learning

Identify the kind of learning algorithm for  “facial identities for facial expressions”.

• Prediction
• Recognition Patterns
• Recognizing Anomalies
• Generating Patterns

Answer explanation

For facial identities and facial expression, “recognition patterns” is used.

Identify the type of learning in which labeled training data is used.

• Semi unsupervised learning
• Supervised learning
• Reinforcement learning
• Unsupervised learning

Answer explanation

Supervised learning uses labeled training data.

Machine learning is a subset of which of the following.

• Artificial Intelligence
• Deep Learning
• Data Learning
• None of these

Answer explanation

Machine Learning is a subset of Artificial Intelligence

Application of machine learning is

• email filtering
• facial recognition
• sentiment analysis
• All of the above

Answer explanation

All of the above

K-Nearest Neighbors (KNN) is classified as what type of machine learning algorithm?

• Instance-based learning
• Parametric learning
• Non-parametric learning
• Model-based learning

Answer explanation

KNN doesn’t build a parametric model of the data. Instead, it directly classifies new data points based on the k nearest points in the training data.

Which of the following is not a supervised machine learning algorithm?

• K-means
• Naïve Bayes
• SVM for classification problems
• Decision tree

Answer explanation

Decision tree, SVM (Support vector machines) for classification problems and Naïve Bayes are the examples of supervised machine learning algorithm. K-means is an example of unsupervised machine learning algorithm.

The learner is trying to predict housing prices based on the size of each house. What type of regression is this?

• Multivariate Logistic Regression
• Logistic Regression
• Linear Regression
• Multivariate Linear Regression

Answer explanation

Learner is trying to predict a discrete number instead of binary output (yes or no / 0 or 1, etc.). Hence, it is a linear regression and not a logistic regression. Since there is only one independent variable, it is not multivariate linear regression.

The learner is trying to predict housing prices based on the size of each house. The variable “size” is

• dependent variable
• label set variable
• independent variable
• target variable

Answer explanation

The variable “size” is not dependent on the price of the house. So, it is an independent variable. The variable “price” is dependent on size.

The target variable is represented along

• Y axis
• X axis
• Either Y-axis or X-axis, it doesn’t matter
• Depends on the dataset

Answer explanation

The target variable is dependent on the other variables. So, it is represented as a function of the independent variable. Thus, it is plotted along the y-axis, after its value is calculated using the function.