Commit d3cb929b64e6c1f7a17f0bac8841d0e37cf41a07
1 parent
522cc08fe8
Exists in
main
change in Beta initialization
Showing 1 changed file with 2 additions and 2 deletions Inline Diff
Main.py
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d3cb929
| from Prediction import Prediction | 1 | 1 | from Prediction import Prediction | |
| import numpy as np | 2 | 2 | import numpy as np | |
| import pandas as pd | 3 | 3 | import pandas as pd | |
| import random | 4 | 4 | import random | |
| from sklearn.metrics import mean_squared_error | 5 | 5 | from sklearn.metrics import mean_squared_error | |
| from sklearn.metrics import mean_absolute_error | 6 | 6 | from sklearn.metrics import mean_absolute_error | |
| from sklearn.metrics import median_absolute_error | 7 | 7 | from sklearn.metrics import median_absolute_error | |
| from math import sqrt | 8 | 8 | from math import sqrt | |
| 9 | 9 | |||
| #Prediction of complexity level (the number of levels is variable) | 10 | 10 | #Prediction of complexity level (the number of levels is variable) | |
| #Each row is a complexity level, each pair [,] is the note and the time for a question (test with 3 levels) | 11 | 11 | #Each row is a complexity level, each pair [,] is the note and the time for a question (test with 3 levels) | |
| 12 | 12 | |||
| dataI=pd.read_csv('dataInitial.csv', sep=' ', header=0) | 13 | 13 | dataI=pd.read_csv('dataInitial.csv', sep=' ', header=0) | |
| data=pd.read_csv('data.csv', sep=' ', header=0) | 14 | 14 | data=pd.read_csv('data.csv', sep=' ', header=0) | |
| v1=[] | 15 | 15 | v1=[] | |
| v2=[] | 16 | 16 | v2=[] | |
| n=0 | 17 | 17 | n=0 | |
| #for name,dr in dataI.iterrows(): | 18 | 18 | #for name,dr in dataI.iterrows(): | |
| for i in range(1): | 19 | 19 | for i in range(1): | |
| 20 | 20 | |||
| #initialization of Beta distribution for all the complexity levels (test with 5 levels) | 21 | 21 | #initialization of Beta distribution for all the complexity levels (test with 5 levels) | |
| betap=[[1,1],[1,2],[1,3],[1,4],[1,5]] | 22 | 22 | betap=[[2,1],[1,2],[1,3],[1,4],[1,5]] | |
| 23 | 23 | |||
| #Parameters: previous grades and times, a-priori paameters for beta distribution in each complexity level, step for change beta parameters, value of penalization for time and value of limit between win and loss | 24 | 24 | #Parameters: previous grades and times, a-priori paameters for beta distribution in each complexity level, step for change beta parameters, value of penalization for time and value of limit between win and loss | |
| pred=Prediction(dataI.iloc[i,:], data.iloc[i,:], betap, 0.2, 1/16, 6) | 25 | 25 | pred=Prediction(dataI.iloc[i,:], data.iloc[i,:], betap, 0.2, 1/16, 6) |