-
Notifications
You must be signed in to change notification settings - Fork 0
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
fix: build histogram x-axis as intervals (a, b] (#4) #5
Open
luigidcsoares
wants to merge
3
commits into
main
Choose a base branch
from
fix/4-histogram-bins
base: main
Could not load branches
Branch not found: {{ refName }}
Could not load tags
Nothing to show
Are you sure you want to change the base?
Some commits from the old base branch may be removed from the timeline,
and old review comments may become outdated.
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
The following example illustrates the new format of the histogram. I'm using the synthetic dataset from the single-dataset example. First, to setup and run the analyses (change the path in import pandas as pd
import sys
sys.path.append("bvm-library")
from bvmlib.bvm import BVM
dataset = pd.DataFrame({
"id": [i for i in range(1, 11)],
"age": [25, 25, 25, 25, 25, 49, 49, 49, 49, 60],
"gender": ["F", "F", "F", "M", "M", "F", "F", "F", "M", "M"],
"grade": ["A", "A", "C", "B", "B", "C", "C", "E", "D", "D"],
"disability": [False, True, True, True, False, True, True, False, False, False]
})
bvm = BVM(dataset)
bvm.qids(["age", "gender"])
bvm.sensitive(["grade", "disability"])
results = bvm.assess() The histogram for re-identification: results["re_id"].loc[0, "Histogram"] Output
The histogram for attribute inference when the sensitive attribute is grade: results["att_inf"].loc[0, "Histogram"] Output
The histogram for attribute inference when the sensitive attribute is disability: results["att_inf"].loc[1, "Histogram"] Output
|
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Closes #4
This PR changes the way histograms are constructed by (i) using intervals as labels for the keys and (ii) using ceil instead of rounding to compute the bins. By using ceil, all values are transformed into the endpoint of the corresponding interval, so reconstructing the interval becomes trivial.