Data Mining Solved MCQs With Answers

By: Prof. Dr. Fazal Rehman | Last updated: August 6, 2024

1.  What is the adaptive system management?

a) machine language techniques

b) machine learning techniques

c) machine procedures techniques

d) none of these

2. An essential process used for applying intelligent methods to extract the data patterns is named as …

a) data mining

b) data analysis

c) data implementation

d) data computation

3. Classification and regression are the properties of…

a) data analysis

b) data manipulation’

c) data mining

d) none of these

4. A class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory is named as …

a) Bayesian classifiers

b) Dijkstra classifiers

c) doppler classifiers

d) all of these

5. Which of the following can be used for finding deep knowledge?

a) stacks

b) algorithms

c) clues

d) none of these

6. We define a ______ as a subdivison  of a set of examples into a number of classes.

a) kingdom

b) tree

c) classification

d) array

7. Group of similar objects that differ significantly from other objects is named as …

a) classification

b) cluster

c) community

d) none of these

8. Combining different type of methods or information is ….

a) analysis

b) computation

c) stack

d) hybrid

9.  What i sthe name of database having a set of databases from different vendors, possibly using different database paradigms?

a) homogeneous database

b) heterogeneous database

c) hybrid database

d) none of these

10. What is the strategic value of data mining?

a) design sensitive

b) cost sensitive

c) technical sensitive

d) time sensitive

11. The amount of information with in data as opposed to the amount of redundancy or noise is known as …

a) paragraph content

b) text content

c) information content

d) none of these

12. What is inductive learning?

a) learning by hypothesis

b) learning by analyzing

c) learning by generalizing

d) none of these

More Next Data Mining MCQs

1. Repeated Data Mining MCQs
2. Classification in Data mining MCQs
3. Clustering in Data mining MCQs
4. Data Analysis and Experimental Design MCQs
5. Basics of Data Science MCQs
6. Big Data MCQs
7. Caret Data Science MCQs 
8. Binary and Count Outcomes MCQs
9. CLI and Git Workflow

 

1. Data Preprocessing MCQs
   • Data Cleaning MCQs
   • Data Integration MCQs
   • Data Transformation MCQs
   • Data Reduction MCQs
2. Data Warehousing and OLAP MCQs
   • Data Warehouse Architecture MCQs
   • Online Analytical Processing (OLAP) MCQs
   • Data Cube Technology MCQs
3. Association Rule Learning MCQs
   • Apriori Algorithm MCQs
   • Eclat Algorithm MCQs
   • FP-Growth Algorithm MCQs
   • Market Basket Analysis MCQs
4. Classification
   • Decision Trees MCQs
   • Naive Bayes MCQs
   • k-Nearest Neighbors (k-NN) MCQs
   • Support Vector Machines (SVM) MCQs
   • Neural Networks MCQs
5. Clustering
   • k-Means Clustering MCQs
   • Hierarchical Clustering MCQs
   • DBSCAN MCQs
   • Mean Shift MCQs
6. Regression MCQs
7. Anomaly Detection MCQs
8. Text Mining and Natural Language Processing (NLP) MCQs
   • Text Preprocessing MCQs
   • Sentiment Analysis MCQs
9. Web Mining MCQs
   • Web Content Mining MCQs
   • Web Structure Mining MCQs
   • Web Usage Mining MCQs
10. Sequential Pattern Mining MCQs
11. Time Series Analysis MCQs

Data Mining Algorithms and Techniques MCQs

13. Frequent Itemset Mining MCQs
    • Apriori Algorithm MCQs
    • FP-Growth Algorithm MCQs
    • Eclat Algorithm MCQs
14. Dimensionality Reduction MCQs
15. Ensemble Methods MCQs
16. Data Mining Tools and Software MCQs
    • WEKA MCQs
    • RapidMiner MCQs
    • KNIME MCQs
    • Orange MCQs
17. Python  Programming for Data Mining MCQs (Pandas, NumPy, Scikit-Learn)
18. R Programming for Data Mining(dplyr, ggplot2, caret) MCQs
19. SQL Programming for Data Mining for Data Mining MCQs
20. Big Data Technologies MCQs
    • Hadoop and MapReduce  MCQs
    • Spark MCQs
    • NoSQL Databases (e.g., MongoDB, Cassandra) MCQs