Question 1

In machine learning, what is the term used for the features or characteristics used to represent instances in a dataset?

Accepted Answer

Attributes

Answer

Models

Answer

Instances

Answer

Datasets

Question 2

In the context of machine learning, what is an 'instance'?

Accepted Answer

A single data point used for training or testing

Answer

A collection of attributes

Answer

A type of algorithm

Answer

A dataset

Question 3

What are the three main components often considered in machine learning regarding data representation?

Accepted Answer

Concepts, Instances, and Attributes

Answer

Algorithms, Models, and Parameters

Answer

Features, Labels, and Outputs

Answer

Training, Testing, and Validation

Question 4

Which of the following defines the term 'dataset' in machine learning?

Accepted Answer

A collection of instances used for analysis

Answer

A tool for data visualization

Answer

A single model for prediction

Answer

A specific type of algorithm

Question 5

Which of the following best describes 'attributes' in a machine learning dataset?

Accepted Answer

Properties or characteristics of instances

Answer

Output labels for classification

Answer

Groups of instances

Answer

Algorithms used for data processing

Question 6

What role do 'instances' play in machine learning?

Accepted Answer

They serve as individual samples for training and testing models

Answer

They define the target variable

Answer

They are types of data preprocessing

Answer

They represent the algorithms used

Question 7

Why is it important to select relevant attributes in a machine learning model?

Accepted Answer

To improve model accuracy and reduce complexity

Answer

To make the model run slower

Answer

To increase data size

Answer

To limit the number of instances

Question 8

In machine learning datasets, what do we call the labels that correspond to instances?

Accepted Answer

Classes

Answer

Instances

Answer

Features

Answer

Attributes

Question 9

Which of the following is a key application of machine learning in marketing?

Accepted Answer

Customer segmentation

Answer

Web development

Answer

Data entry automation

Answer

Supply chain management

Question 10

Which of the following is a common application of machine learning in healthcare?

Accepted Answer

Predictive analytics for patient diagnoses

Answer

Manufacturing automation

Answer

Email spam filtering

Answer

Social media marketing

Question 11

In which sector is machine learning commonly used for fraud detection?

Accepted Answer

Banking and finance

Answer

Manufacturing

Answer

Education

Answer

Agriculture

Question 12

What is the main difference between supervised and unsupervised learning?

Accepted Answer

Supervised learning uses labeled data while unsupervised learning uses unlabeled data

Answer

Supervised learning only works with structured data

Answer

Unsupervised learning is more accurate than supervised learning

Answer

Supervised learning requires human intervention, while unsupervised does not

Question 13

What is the primary goal of supervised learning in machine learning?

Accepted Answer

To learn a function that maps inputs to outputs based on labeled training data

Answer

To find patterns in unstructured data

Answer

To cluster data without any labels

Answer

To reduce the dimensionality of the data

Question 14

Which algorithm is primarily used for classification tasks in machine learning?

Accepted Answer

Support Vector Machine (SVM)

Answer

K-means Clustering

Answer

Linear Regression

Answer

Principal Component Analysis (PCA)

Question 15

What is overfitting in the context of machine learning?

Accepted Answer

A model that performs well on training data but poorly on unseen data

Answer

A model that ignores the training data

Answer

A model that simplifies the learning process

Answer

A model that accurately predicts new data

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