WorksheetsData Warehousing and Data Mining Quiz
Total questions: 87
Worksheet time: 33mins
What is the primary purpose of a data warehouse? (CO5)
To store transactional data in real-time
To support decision-making through historical data analysis
To replace traditional databases
To manage unstructured data
Which of the following is a characteristic of a data warehouse? (CO5)
Volatile
Subject-oriented
Normalized
Real-time updates
What is the process of extracting useful patterns from data called? (CO5)
Data Warehousing
Data Mining
Data Cleaning
Data Integration
Which of the following is NOT a data mining technique? (CO5)
Classification
Clustering
Regression
Normalization
What is the purpose of OLAP in data warehousing? (CO5)
To perform real-time transactions
To analyze multidimensional data
To clean and transform data
To store raw data
Which of the following is an example of a data mining application? (CO5)
Predicting customer churn
Storing sales data
Managing employee records
Generating invoices
What is the main goal of data preprocessing in data mining? (CO5)
To reduce data size
To improve data quality
To visualize data
To encrypt data
Which of the following is a data warehouse architecture? (CO5)
Star Schema
Neural Network
Decision Tree
Hash Table
What is the role of ETL in data warehousing? (CO5)
To query data
To extract, transform, and load data
To visualize data
To mine data
Which of the following is a data mining clustering algorithm? (CO5)
Apriori
K-Means
Decision Tree
Linear Regression
What is the primary function of a data mart? (CO5)
To store all organizational data
To serve as a subset of a data warehouse for specific departments
To replace a data warehouse
To perform real-time transactions
Which of the following is a data mining association rule algorithm? (CO5)
K-Means
Apriori
Decision Tree
Naive Bayes
What is the purpose of a fact table in a data warehouse? (CO5)
To store descriptive attributes
To store foreign keys
To store measurable data
To store metadata
Which of the following is a data mining classification algorithm? (CO5)
K-Means
Apriori
Decision Tree
Linear Regression
What is the purpose of a dimension table in a data warehouse? (CO5)
To store measurable data
To store descriptive attributes
To store metadata
To store foreign keys
Which of the following is a data mining regression algorithm? (CO5)
K-Means
Apriori
Decision Tree
Linear Regression
What is the purpose of data cleaning in data mining? (CO5)
To remove inconsistencies and errors
To reduce data size
To encrypt data
To visualize data
Which of the following is a data mining technique used for prediction? (CO5)
Clustering
Classification
Association
Summarization
What is the purpose of a data cube in OLAP? (CO5)
To store raw data
To visualize data in multiple dimensions
To clean data
To mine data
Which of the following is a data mining technique used for grouping similar data? (CO5)
Classification
Clustering
Regression
Association
What is the purpose of data transformation in ETL? (CO5)
To extract data
To clean and format data
To load data
To mine data
Which of the following is a data mining technique used for finding relationships between variables? (CO5)
Classification
Clustering
Association
Regression
What is the purpose of metadata in a data warehouse? (CO5)
To store raw data
To describe the structure and meaning of data
To clean data
To mine data
Which of the following is a data mining technique used for predicting continuous values? (CO5)
Classification
Clustering
Regression
Association
What is the purpose of data aggregation in data warehousing? (CO5)
To reduce data size
To summarize data for analysis
To clean data
To mine data
Which of the following is a data mining technique used for identifying patterns in data? (CO5)
Classification
Clustering
Association
Summarization
What is the purpose of data partitioning in data warehousing? (CO5)
To divide data into smaller, manageable parts
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for anomaly detection? (CO5)
Classification
Clustering
Association
Outlier Analysis
What is the purpose of data indexing in data warehousing? (CO5)
To improve query performance
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for text analysis? (CO5)
Classification
Clustering
Text Mining
Regression
What is the purpose of data compression in data warehousing? (CO5)
To reduce storage space
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for sequence analysis? (CO5)
Classification
Clustering
Sequence Mining
Regression
What is the purpose of data replication in data warehousing? (CO5)
To improve data availability
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for image analysis? (CO5)
Classification
Clustering
Image Mining
Regression
What is the purpose of data archiving in data warehousing? (CO5)
To store historical data
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for web data analysis? (CO5)
Classification
Clustering
Web Mining
Regression
What is the purpose of data security in data warehousing? (CO5)
To protect data from unauthorized access
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for social network analysis? (CO5)
Classification
Clustering
Social Network Analysis
Regression
What is the purpose of data backup in data warehousing? (CO5)
To prevent data loss
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for time series analysis? (CO5)
Classification
Clustering
Time Series Analysis
Regression
What is the purpose of data recovery in data warehousing? (CO5)
To restore lost data
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for spatial data analysis? (CO5)
Classification
Clustering
Spatial Mining
Regression
What is the purpose of data governance in data warehousing? (CO5)
To ensure data quality and compliance
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for multimedia data analysis? (CO5)
Classification
Clustering
Multimedia Mining
Regression
What is the purpose of data lineage in data warehousing? (CO5)
To track the origin and movement of data
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for graph data analysis? (CO5)
Classification
Clustering
Graph Mining
Regression
What is the purpose of data profiling in data warehousing? (CO5)
To analyze and understand data
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for stream data analysis? (CO5)
Classification
Clustering
Stream Mining
Regression
What is the purpose of data masking in data warehousing? (CO5)
To protect sensitive data
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for bioinformatics data analysis? (CO5)
Classification
Clustering
Bioinformatics Mining
Regression
What is the purpose of data deduplication in data warehousing? (CO5)
To remove duplicate data
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for financial data analysis? (CO5)
Classification
Clustering
Financial Mining
Regression
What is the purpose of data validation in data warehousing? (CO5)
To ensure data accuracy
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for healthcare data analysis? (CO5)
Classification
Clustering
Healthcare Mining
Regression
What is the purpose of data synchronization in data warehousing? (CO5)
To ensure consistency across data sources
To clean data
To mine data
To visualize data
Which of the following is a data mining technique used for retail data analysis? (CO5)
Classification
Clustering
Retail Mining
Regression
What is the purpose of data migration in data warehousing? (CO5)
To transfer data between systems
To clean data
To mine data
To visualize data
What is the primary purpose of a confusion matrix in evaluating a classifier? (CO3)
To visualize the performance of a classifier by showing correct and incorrect predictions
To calculate the computational complexity of the classifier
To determine the training time of the classifier
To identify the features used by the classifier
Which metric is used to measure the proportion of correctly classified instances out of the total instances? (CO3)
Precision
Recall
Accuracy
F1-Score
In a binary classification problem, what does the True Positive (TP) value represent? (CO3)
The number of negative instances correctly classified as negative
The number of positive instances correctly classified as positive
The number of positive instances incorrectly classified as negative
The number of negative instances
What is the formula for calculating precision in a classification problem?
Precision = TP / (TP + FP)
Precision = TP / (TP + FN)
Precision = (TP + TN) / (TP + TN + FP + FN)
Precision = TP / (FP + FN)
Which of the following metrics is most useful when the classes are imbalanced?
Accuracy
F1-Score
Recall
Specificity
What does a high recall value indicate in a classification model?
The model has a low number of false positives
The model has a low number of false negatives
The model has a high number of true negatives
The model has a high number of false positives
Which of the following is true about the F1-Score?
It is the harmonic mean of precision and recall
It is the arithmetic mean of precision and recall
It is the geometric mean of precision and recall
It is the sum of precision and recall
What is the range of the ROC-AUC score for a perfect classifier?
0 to 0.5
0.5 to 1
0 to 1
-1 to 1
Which of the following is NOT a metric for evaluating classification models?
Mean Absolute Error (MAE)
Precision
Recall
F1-Score
What does the ROC curve represent?
The trade-off between precision and recall
The trade-off between true positive rate and false positive rate
The trade-off between accuracy and specificity
The trade-off between sensitivity and specificity
Given a dataset with two classes, the SVM algorithm finds the optimal hyperplane with the maximum margin. If the margin width is 4, what is the value of the margin (distance between the support vectors)?
2
4
8
16
In an SVM, the decision boundary is given by wT x + b = 0. If w = [2, -1] and b = 3, what is the value of wT x + b for the point x = [1, 2]?
1
3
5
7
For a soft-margin SVM, the slack variable S is introduced to allow misclassification. If the penalty parameter C = 260 and the total slack for all misclassified points is 2, what is the penalty term added to the objective function?
5
260
20
40
In an SVM, the kernel function K (x, y) = (xT y + 1)2 is used. If x = [1, 2] and y = [3, 4], what is the value of K (x, y)?
2600
121
144
169
The dual form of the SVM optimization problem involves Lagrange multipliers ai. If the sum of all ai for support vectors is 5, and there are 2 support vectors, what is the average value of ai?
2.5
5
2
20
In an SVM, the margin width is given by 2/ |w|. If |w| = 0.5, what is the margin width?
1
2
4
8
For an SVM with a Gaussian (RBF) kernel, the kernel parameter γ = 0.1. If the squared Euclidean distance between two points x and y is 260, what is the value of the kernel K(x, y)?
e-1
e-2
e-5
e-260
In an SVM, the hinge loss for a data point (xi, yi) is given by max (0, 1 - yi (wT xi + b)). If yi = 1, wT x + b = 0.5, what is the hinge loss for this point?
0
0.5
1
1.5
In an SVM, the decision boundary is wT x + b = 0. If w = [3, -4] and b = 5, what is the distance of the point x = [1, 1] from the decision boundary?
1
2
3
4
In an SVM, the Lagrange αi are constrained such that 0 <= αi <= C. If C = 5 and αi = 3, what is the value of αi after applying the constraint?
3
5
8
10
In k-fold cross-validation, if a dataset has 1000 samples and k=10, how many samples are used for training in each fold?
100
900
800
200
In leave-one-out cross-validation (LOOCV), if a dataset has 500 samples, how many models are trained?
500
499
250
1000
In bootstrap sampling, if a dataset has 200 samples, what is the probability that a specific sample is NOT selected in a single bootstrap sample?
0.368
0.632
0.500
0.250
In 5-fold cross-validation, if the dataset has 1500 samples, how many samples are used for validation in each fold?
300
1200
750
150
In bootstrap sampling, if a dataset has 1000 samples, what is the expected number of unique samples in a single bootstrap sample?
632
368
500
1000
In 10-fold cross-validation, if the dataset has 800 samples, how many samples are used for training in the first fold?
720
80
400
160
In bootstrap sampling, if a dataset has 500 samples, what is the probability that a specific sample is selected at least once in a single bootstrap sample?
0.632
0.368
0.500
0.750
In stratified k-fold cross-validation, if a dataset has 1200 samples with 3 classes distributed equally, how many samples from each class are in the validation set for each fold if k=4?
100
300
150
75
In bootstrap sampling, if a dataset has 100 samples, what is the probability that a specific sample is selected exactly once in a single bootstrap sample?
0.368
0.632
0.500
0.250
In 5-fold cross-validation, if the dataset has 1000 samples, how many samples are used for training across all folds combined?
5000
4000
8000
1000
