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the smaller the value of beta is ,the more difficult the item is ? #20
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I think there is a mistake in the library (maybe the real b is from pyirt import irt
from pprint import pprint
item_param, user_param = irt([
(1, 1, 0), (1, 2, 1), (1, 3, 1),
(2, 1, 0), (2, 2, 1), (2, 3, 0),
(3, 1, 0), (2, 2, 1), (2, 3, 1),
])
pprint(item_param)
# {1: {'alpha': 0.25, 'beta': -2.0, 'c': 0.0},
# 2: {'alpha': 0.5720948359800555, 'beta': 2.0, 'c': 0.0},
# 3: {'alpha': 0.25, 'beta': 0.634102890032698, 'c': 0.0}}
pprint(user_param)
# {1: 0.13484234439295528, 2: 0.07287218993120267, 3: 0.019347314772223796} Based on the original paper in equation (4), the probability of successfully answering questions is as follows: Since |
hi ,there is a problem which confuse me a few of days .i run code as follows:
res = irt(data)
i check many items in the data. when the beta is smaller such as -1.9,-2 , but the liked rate of this item is very low which i think it should be more large.when the beta is bigger such as 1.9 , 2 ,but the liked rate of this item is very high which i think it should be smaller. could anyone explain sth to me when the beta is large ,the liked rate should be large or smaller. note: the liked rate equals the number of "1" divide all numbers of items .
the format of the data is as follows :
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