Orange MCQs

By: Prof. Dr. Fazal Rehman Shamil | Last updated: August 7, 2024

1. What is Orange primarily used for in data mining?
a) Image processing
b) Video editing
c) Data visualization, analysis, and machine learning
d) Database management

Answer: c) Data visualization, analysis, and machine learning

2. What type of interface does Orange provide for building data workflows?
a) Command-line interface
b) Text-based interface
c) Graphical user interface (GUI) with drag-and-drop features
d) Code editor interface

Answer: c) Graphical user interface (GUI) with drag-and-drop features

3. In Orange, what is a “Widget”?
a) A programming function
b) A graphical representation of a step in a workflow
c) A data storage unit
d) A visualization tool

Answer: b) A graphical representation of a step in a workflow

4. Which of the following file formats can be imported into Orange for analysis?
a) .csv
b) .xlsx
c) .txt
d) All of the above

Answer: d) All of the above

5. What is the purpose of the “File” widget in Orange?
a) To preprocess the data
b) To load data from external sources
c) To visualize the data
d) To perform clustering

Answer: b) To load data from external sources

6. Which Orange widget is used for data visualization?
a) Data Table
b) Scatter Plot
c) Decision Tree
d) K-Means

Answer: b) Scatter Plot

7. How can you share a workflow created in Orange?
a) Exporting it as an .ows file
b) Taking a screenshot of the workflow
c) Printing the workflow diagram
d) Writing down the steps manually

Answer: a) Exporting it as an .ows file

8. Which of the following is a feature of Orange?
a) Text mining
b) Image analysis
c) Network analysis
d) All of the above

Answer: d) All of the above

9. What is the purpose of the “Select Columns” widget in Orange?
a) To visualize data
b) To select and filter the columns of a dataset
c) To classify data into categories
d) To apply machine learning algorithms

Answer: b) To select and filter the columns of a dataset

10. Which machine learning algorithms are available in Orange?
a) Decision Trees
b) Support Vector Machines (SVM)
c) Neural Networks
d) All of the above

Answer: d) All of the above

11. In Orange, what does the “Classification Tree” widget do?
a) Preprocess data
b) Visualize data
c) Build and visualize decision trees for classification
d) Cluster data

Answer: c) Build and visualize decision trees for classification

12. How can you handle missing values in a dataset in Orange?
a) Using the “Impute” widget
b) Using the “Decision Tree” widget
c) Using the “K-Means” widget
d) Using the “SVM” widget

Answer: a) Using the “Impute” widget

13. What is a common application of Orange in business?
a) Web design
b) Market basket analysis
c) Video production
d) Graphic design

Answer: b) Market basket analysis

14. In Orange, what is the “Pivot Table” widget used for?
a) To visualize the relationship between two variables
b) To summarize data in a tabular form
c) To apply machine learning algorithms
d) To preprocess data

Answer: b) To summarize data in a tabular form

15. Which Orange widget allows for model evaluation and validation?
a) Test & Score
b) Scatter Plot
c) File
d) K-Means

Answer: a) Test & Score

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
  2. Data Warehousing and OLAP MCQs
  3. Association Rule Learning MCQs
  4. Classification
  5. Clustering
  6. Regression MCQs
  7. Anomaly Detection MCQs
  8. Text Mining and Natural Language Processing (NLP) MCQs
  9. Web Mining MCQs
  10. Sequential Pattern Mining MCQs
  11. Time Series Analysis MCQs

Data Mining Algorithms and Techniques MCQs

  1. Frequent Itemset Mining MCQs
  2. Dimensionality Reduction MCQs
  3. Ensemble Methods MCQs
  4. Data Mining Tools and Software MCQs
  5. Python  Programming for Data Mining MCQs (Pandas, NumPy, Scikit-Learn)
  6. R Programming for Data Mining(dplyr, ggplot2, caret) MCQs
  7. SQL Programming for Data Mining for Data Mining MCQs
  8. Big Data Technologies MCQs