________ are the devices that request and render web contents.

• A) Applications
• B) Providers
• C) Clients
• D) Servers

_________are special websites that have indexed billions of pages - and make it easy for you to find a website or page in an instant.

• A) Web applications
• B) Web users
• C) Web browsers
• D) Search engines

________ are the applications that deliver web contents or services to __________.

• A) Clients, Servers
• B) Consumer, Providers
• C) Users, Applications
• D) Servers, Clients

We define the idf (inverse document frequency) of t by______.

• A) \(idf_{t} df_{t}/N = log_{10}\)
• B) \(idf_{t} = log_{10}N/df_{t}\)
• C) \(idf_{t} = log_{10}df_{t}/N\)
• D) \(idf_{t} log_{10}= N/df_{t}\)

There are ______ types of retrieval models.

• A) 4
• B) 3
• C) 2
• D) 1

It is better to ____________ stop words before indexing.

• A) Ignore
• B) Update
• C) Remove
• D) Insert

Which function is used by Logistic Regression to estimate optimal model parameters?

• A) Maximum Likelihood Estimation (MLE)
• B) Mean Absolute Error (MAE)
• C) Least Squares Function
• D) Entropy Gain Function

Which is a common dimensionality reduction technique in unsupervised learning?

• A) SVM
• B) Decision Trees
• C) PCA
• D) Gradient Boosting

Why does Logistic Regression restrict outputs between 0 and 1?

• A) To allow multiple continuous outputs
• B) To represent probabilities of class membership
• C) To convert images into text
• D) To reduce processing time

Which of the following is a correct real-world application of anomaly detection?

• A) Forecasting next month’s sales
• B) Detecting fraudulent credit card transactions
• C) Classifying emails into categories
• D) Grouping news articles by topic

Which of the following best describes unsupervised learning?

• A) Learning through teacher feedback
• B) Learning from labeled data to predict a target variable
• C) Learning using reinforcement signals
• D) Learning from unlabeled data to find hidden structure

Which of the following is a major challenge in anomaly detection?

• A) The definition of normal and abnormal can change over time
• B) Anomalies always follow a predictable pattern
• C) Easy availability of labelled anomaly samples
• D) Anomalies occur frequently in datasets

Anomaly detection techniques are especially useful when:

• A) The number of normal samples is much higher than abnormal ones
• B) The dataset contains no noise
• C) There are no patterns in the data
• D) All classes have balanced representation

Which distance metric is most commonly used in K-Means?

• A) Jaccard distance
• B) Hamming distance
• C) Euclidean distance
• D) Manhattan distance

What type of problem is Logistic Regression primarily used for?

• A) Classification of categorical outcomes
• B) Recommending products based on behavior
• C) Clustering similar groups in data
• D) Predicting continuous values such as house prices

K-Means is a type of:

• A) Regression technique
• B) Reinforcement learning algorithm
• C) Supervised learning algorithm
• D) Unsupervised clustering algorithm

Which of the following is a correct example of binary classification using Logistic Regression?

• A) Forecasting stock prices in rupees
• B) Determining if a patient is Healthy/Sick
• C) Grouping customers into multiple clusters
• D) Predicting exact temperature for tomorrow

A company wants to group customers into segments based on annual spending and income. Which technique is most suitable?

• A) Naive Bayes
• B) Linear Regression
• C) Logistic Regression
• D) K-Means Clustering

A retail company wants to group customers based on shopping patterns to target personalized promotions. Which unsupervised method is most suitable?

• A) Logistic Regression
• B) Naive Bayes Classification
• C) K-Means Clustering
• D) Linear Regression

A network security team wants to detect abnormal spikes in incoming traffic that might indicate a cyberattack. Which anomaly detection approach is appropriate?

• A) K-Means clustering
• B) Regression analysis
• C) Linear classification only
• D) Statistical deviation–based detection