School Grades

School Grades

Predict grades of school students based on lifestyle attributes




Instances: 649

Attributes: 33

Tasks: Classification, Regression

Downloads: 1349

Year Published: 2008

Missing Values: No


Attribute Details:
Name Type Description
school string student's school (binary: "GP" Gabriel Pereira or "MS" Mousinho da Silveira)
sex string student's sex (binary: "F" female or "M" male)
age integer student's age (numeric: from 15 to 22)
address string student's home address type (binary: "U" urban or "R" rural)
famsize string family size (binary: "LE3" less or equal to 3 or "GT3" greater than 3)
Pstatus string parent's cohabitation status (binary: "T" living together or "A" apart)
Medu integer mother's education (numeric: 0: none, 1: primary education (4th grade), 2: 5th to 9th grade, 3 _ secondary education or 4 _ higher education)
Fedu integer father's education (numeric: 0 - none, 1 - primary education (4th grade), 2 _ 5th to 9th grade, 3 _ secondary education or 4 _ higher education)
Mjob string mother's job (nominal: "teacher", "health" care related, civil "services" (e.g. administrative or police), "at_home" or "other")
Fjob string father's job (nominal: "teacher", "health" care related, civil "services" (e.g. administrative or police), "at_home" or "other")
reason string reason to choose this school (nominal: close to "home", school "reputation", "course" preference or "other")
guardian string student's guardian (nominal: "mother", "father" or "other")
traveltime integer home to school travel time (numeric: 1 - <15 min., 2 - 15 to 30 min., 3 - 30 min. to 1 hour, or 4 - >1 hour)
studytime integer weekly study time (numeric: 1 - <2 hours, 2 - 2 to 5 hours, 3 - 5 to 10 hours, or 4 - >10 hours)
G3 integer Predictor Class: final grade (numeric: from 0 to 20)

Showing 15 out of 33 attributes. Download attribute CSV for full details





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SAMPLE VALUES


school sex age address famsize Pstatus Medu Fedu Mjob Fjob reason guardian traveltime studytime G3
GP F 18 U GT3 A 4 4 at_home teacher course mother 2 2 11
GP F 17 U GT3 T 1 1 at_home other course father 1 2 11
GP F 15 U LE3 T 1 1 at_home other other mother 1 2 12
GP F 15 U GT3 T 4 2 health services home mother 1 3 14

Showing 15 out of 33 attributes. Download attribute CSV for full details








DETAILS


Description

This data approach student achievement in secondary education of two Portuguese schools. The data attributes include student grades, demographic, social and school related features) and it was collected by using school reports and questionnaires. Two datasets are provided regarding the performance in two distinct subjects: Mathematics (mat) and Portuguese language (por). In [Cortez and Silva, 2008], the two datasets were modeled under binary/five-level classification and regression tasks. Important note: the target attribute G3 has a strong correlation with attributes G2 and G1. This occurs because G3 is the final year grade (issued at the 3rd period), while G1 and G2 correspond to the 1st and 2nd period grades. It is more difficult to predict G3 without G2 and G1, but such prediction is much more useful (see paper source for more details).


X Decoder Tables

Column Name One Hot Val Decoded Val
school 1,0 GP
school 0,1 MS
sex 1,0 F
sex 0,1 M
address 1,0 R
address 0,1 U
famsize 1,0 GT3
famsize 0,1 LE3
Pstatus 1,0 A
Pstatus 0,1 T
Mjob 0,0,1,0,0 other
Mjob 0,1,0,0,0 health
Mjob 1,0,0,0,0 at_home
Mjob 0,0,0,0,1 teacher
Mjob 0,0,0,1,0 services
Fjob 0,0,1,0,0 other
Fjob 0,1,0,0,0 health
Fjob 1,0,0,0,0 at_home
Fjob 0,0,0,0,1 teacher
Fjob 0,0,0,1,0 services
reason 0,1,0,0 home
reason 0,0,1,0 other
reason 1,0,0,0 course
reason 0,0,0,1 reputation
guardian 0,0,1 other
guardian 1,0,0 father
guardian 0,1,0 mother
schoolsup 1,0 no
schoolsup 0,1 yes
famsup 1,0 no
famsup 0,1 yes
paid 1,0 no
paid 0,1 yes
activities 1,0 no
activities 0,1 yes
nursery 1,0 no
nursery 0,1 yes
higher 1,0 no
higher 0,1 yes
internet 1,0 no
internet 0,1 yes
romantic 1,0 no
romantic 0,1 yes
Column Name Label Val Decoded Val
school 0 GP
school 1 MS
sex 0 F
sex 1 M
address 0 R
address 1 U
famsize 0 GT3
famsize 1 LE3
Pstatus 0 A
Pstatus 1 T
Mjob 0 at_home
Mjob 1 health
Mjob 2 other
Mjob 3 services
Mjob 4 teacher
Fjob 0 at_home
Fjob 1 health
Fjob 2 other
Fjob 3 services
Fjob 4 teacher
reason 0 course
reason 1 home
reason 2 other
reason 3 reputation
guardian 0 father
guardian 1 mother
guardian 2 other
schoolsup 0 no
schoolsup 1 yes
famsup 0 no
famsup 1 yes
paid 0 no
paid 1 yes
activities 0 no
activities 1 yes
nursery 0 no
nursery 1 yes
higher 0 no
higher 1 yes
internet 0 no
internet 1 yes
romantic 0 no
romantic 1 yes

LICENSE

UCI Machine Learning Repository

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.






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