Using Python to Implement the Data Analysis for Dropout Rates and Course Performances of Multiple-Enrolled Students
碩士 === 南華大學 === 資訊管理學系 === 107 === In view of the impact of the domestic minority, college students in D.C. 2006 to 2016 years showed negative growth, enrollment increasingly competition, if the loss of students in school, the school is a big help. This study uses the data mining technology to fin...
Main Authors: | WU, ZIH-HAO, 吳梓豪 |
---|---|
Other Authors: | CHIU, HUNG-PIN |
Format: | Others |
Language: | zh-TW |
Published: |
2019
|
Online Access: | http://ndltd.ncl.edu.tw/handle/b9gd94 |
Similar Items
-
A Study on Dropout Rates and Course Performances of Multiple-enrolled Students Using Data Mining Techniques
by: LIN, CHING-HAN, et al.
Published: (2017) -
Predicting Computer Engineering students' dropout in Cuban Higher Education with pre-enrollment and early performance data
by: Niurys Lázaro Alvarez, et al.
Published: (2020-09-01) -
Teaching Practice of Python Programming Course in Big Data Era
by: Liu Qing
Published: (2019-01-01) -
Status and determinants of enrollment and dropout of health insurance in Nepal: an explorative study
by: Chhabi Lal Ranabhat, et al.
Published: (2020-10-01) -
Negotiating education for many : enrolment, dropout and persistence in the community schools of Kolondieba, Mali
by: Laugharn, Peter Andrew
Published: (2002)