To see the results, view result.ipynb
Abstract:
It is the real dataset about the students' knowledge status about the subject of Electrical DC Machines. The dataset had been obtained from Ph.D. Thesis.
Data Set Information:
The users' knowledge class were classified by the authors
using intuitive knowledge classifier (a hybrid ML technique of k-NN and meta-heuristic exploring methods), k-nearest neighbor algorithm.
See article for more details on how the users' data was collected and evaluated by the user modeling server.
H. T. Kahraman, Sagiroglu, S., Colak, I., Developing intuitive knowledge classifier and modeling of users' domain dependent data in web, Knowledge Based Systems, vol. 37, pp. 283-295, 2013.
| Attribute Information: |
|---|
| STG (The degree of study time for goal object materails), |
| SCG (The degree of repetition number of user for goal object materails) |
| STR (The degree of study time of user for related objects with goal object) |
| LPR (The exam performance of user for related objects with goal object) |
| PEG (The exam performance of user for goal objects) |
| UNS (The knowledge level of user) |
| Data Set Characteristics: Multivariate |
|---|
| Number of Instances: 403 |
| Area: Education |
| Attribute Characteristics: Real |
| Number of Attributes: 5 |
| Associated Tasks: Classification |
| Class Distribution |
| Very Low: 50 |
| Low:129 |
| Middle: 122 |
| high 130 |
| Total:403 |
. T. Kahraman, Sagiroglu, S., Colak, I., Developing intuitive knowledge classifier and modeling of users' domain dependent data in web, Knowledge Based Systems, vol. 37, pp. 283-295, 2013.
Dataset link : http://archive.ics.uci.edu/ml/datasets/User+Knowledge+Modeling?fbclid=IwAR3tfduwlL5iocAW-_GpR1ZlOXc6CcJAIiMNlZUspHWe7ZcuSOM2F1Cy2go
Done By:
Mohamed Gohar : https://github.com/MohamedGoharFCIH
Muhammad Badawy : https://github.com/muhammadBadawy