Select Language

AI社区

公开数据集

学生酒精消费

学生酒精消费

0.11M
246 浏览
0 喜欢
0 次下载
0 条讨论
Universities and Colleges,Public Health,Primary and Secondary Schools Classification

数据结构 ? 0.11M

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Context:

    The data were obtained in a survey of students math and portuguese language courses in secondary school. It contains a lot of interesting social, gender and study information about students. You can use it for some EDA or try to predict students final grade.

    Content:

    Attributes for both student-mat.csv (Math course) and student-por.csv (Portuguese language course) datasets: 1. school - student's school (binary: 'GP' - Gabriel Pereira or 'MS' - Mousinho da Silveira) 2. sex - student's sex (binary: 'F' - female or 'M' - male) 3. age - student's age (numeric: from 15 to 22) 4. address - student's home address type (binary: 'U' - urban or 'R' - rural) 5. famsize - family size (binary: 'LE3' - less or equal to 3 or 'GT3' - greater than 3) 6. Pstatus - parent's cohabitation status (binary: 'T' - living together or 'A' - apart) 7. Medu - mother's education (numeric: 0 - none, 1 - primary education (4th grade), 2 – 5th to 9th grade, 3 – secondary education or 4 – higher education) 8. Fedu - father's education (numeric: 0 - none, 1 - primary education (4th grade), 2 – 5th to 9th grade, 3 – secondary education or 4 – higher education) 9. Mjob - mother's job (nominal: 'teacher', 'health' care related, civil 'services' (e.g. administrative or police), 'at_home' or 'other') 10. Fjob - father's job (nominal: 'teacher', 'health' care related, civil 'services' (e.g. administrative or police), 'at_home' or 'other') 11. reason - reason to choose this school (nominal: close to 'home', school 'reputation', 'course' preference or 'other') 12. guardian - student's guardian (nominal: 'mother', 'father' or 'other') 13. traveltime - home to school travel time (numeric: 1 - <15 min., 2 - 15 to 30 min., 3 - 30 min. to 1 hour, or 4 - >1 hour) 14. studytime - weekly study time (numeric: 1 - <2 hours, 2 - 2 to 5 hours, 3 - 5 to 10 hours, or 4 - >10 hours) 15. failures - number of past class failures (numeric: n if 1<=n<3, else 4) 16. schoolsup - extra educational support (binary: yes or no) 17. famsup - family educational support (binary: yes or no) 18. paid - extra paid classes within the course subject (Math or Portuguese) (binary: yes or no) 19. activities - extra-curricular activities (binary: yes or no) 20. nursery - attended nursery school (binary: yes or no) 21. higher - wants to take higher education (binary: yes or no) 22. internet - Internet access at home (binary: yes or no) 23. romantic - with a romantic relationship (binary: yes or no) 24. famrel - quality of family relationships (numeric: from 1 - very bad to 5 - excellent) 25. freetime - free time after school (numeric: from 1 - very low to 5 - very high) 26. goout - going out with friends (numeric: from 1 - very low to 5 - very high) 27. Dalc - workday alcohol consumption (numeric: from 1 - very low to 5 - very high) 28. Walc - weekend alcohol consumption (numeric: from 1 - very low to 5 - very high) 29. health - current health status (numeric: from 1 - very bad to 5 - very good) 30. absences - number of school absences (numeric: from 0 to 93) These grades are related with the course subject, Math or Portuguese: 31. G1 - first period grade (numeric: from 0 to 20) 31. G2 - second period grade (numeric: from 0 to 20) 32. G3 - final grade (numeric: from 0 to 20, output target) **Additional note:** there are several (382) students that belong to both datasets . These students can be identified by searching for identical attributes that characterize each student, as shown in the annexed R file.

    Source Information

    P. Cortez and A. Silva. Using Data Mining to Predict Secondary School Student Performance. In A. Brito and J. Teixeira Eds., Proceedings of 5th FUture BUsiness TEChnology Conference (FUBUTEC 2008) pp. 5-12, Porto, Portugal, April, 2008, EUROSIS, ISBN 978-9077381-39-7. Fabio Pagnotta, Hossain Mohammad Amran. Email:fabio.pagnotta@studenti.unicam.it, mohammadamra.hossain '@' studenti.unicam.it University Of Camerino https://archive.ics.uci.edu/ml/datasets/STUDENT+ALCOHOL+CONSUMPTION
    ×

    帕依提提提温馨提示

    该数据集正在整理中,为您准备了其他渠道,请您使用

    注:部分数据正在处理中,未能直接提供下载,还请大家理解和支持。
    暂无相关内容。
    暂无相关内容。
    • 分享你的想法
    去分享你的想法~~

    全部内容

      欢迎交流分享
      开始分享您的观点和意见,和大家一起交流分享.
    所需积分:0 去赚积分?
    • 246浏览
    • 0下载
    • 0点赞
    • 收藏
    • 分享