ALalbertzeyer·Jun 23, 2013Submission
FuzzyInfer - predicts one or more unknown characteristics via Fuzzy set analysis
1 points · Open discussionseamusabshere
fuzzy_infer
Ruby2012–2013
seamusabshere / fuzzy_infer
fuzzy_infer
Fuzzy set analysis - predicts one or more unknown characteristics of an input case by comparing its known characteristics to a reference dataset whose records contain both the known and unknown characteristics.
2Distinct people
2Mentions
0Explicit recommenders
8GitHub stars
What to know before exploring
What it is
Fuzzy set analysis - predicts one or more unknown characteristics of an input case by comparing its known characteristics to a reference dataset whose records contain both the known and unknown characteristics.
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
No recommendation phrase was found in the indexed comments.
No classified warning is attached to this page. Read the discussions before treating silence as approval.
Also in these discussions
No other repository is repeatedly linked in the same discussions.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by month2 dated mentions
Observed mentions: 2012-04-16 16:05:51 UTC to 2013-06-23 17:50:41 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Apr 2012 | 2012-04-01 00:00:00 UTC | 2012-05-01 00:00:00 UTC | 1 | 0 | 1 |
| May 2012 | 2012-05-01 00:00:00 UTC | 2012-06-01 00:00:00 UTC | 0 | 0 | 0 |
| Jun 2012 | 2012-06-01 00:00:00 UTC | 2012-07-01 00:00:00 UTC | 0 | 0 | 0 |
| Jul 2012 | 2012-07-01 00:00:00 UTC | 2012-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2012 | 2012-08-01 00:00:00 UTC | 2012-09-01 00:00:00 UTC | 0 | 0 | 0 |
| Sep 2012 | 2012-09-01 00:00:00 UTC | 2012-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2012 | 2012-10-01 00:00:00 UTC | 2012-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2012 | 2012-11-01 00:00:00 UTC | 2012-12-01 00:00:00 UTC | 0 | 0 | 0 |
| Dec 2012 | 2012-12-01 00:00:00 UTC | 2013-01-01 00:00:00 UTC | 0 | 0 | 0 |
| Jan 2013 | 2013-01-01 00:00:00 UTC | 2013-02-01 00:00:00 UTC | 0 | 0 | 0 |
| Feb 2013 | 2013-02-01 00:00:00 UTC | 2013-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2013 | 2013-03-01 00:00:00 UTC | 2013-04-01 00:00:00 UTC | 0 | 0 | 0 |
| Apr 2013 | 2013-04-01 00:00:00 UTC | 2013-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2013 | 2013-05-01 00:00:00 UTC | 2013-06-01 00:00:00 UTC | 0 | 0 | 0 |
| Jun 2013 | 2013-06-01 00:00:00 UTC | 2013-07-01 00:00:00 UTC | 1 | 1 | 0 |
What Hacker News says
2 sourcesMy for-profit company (Brighter Planet) often gets product ideas from our data scientists; it's exactly what Dr. Haghighi is talking about.
For example: trying to model environmental impact of Bill Gates's 66,000 sq ft house during a hackathon -> discovery that we need fuzzy set analysis (https://github.com/seamusabshere/fuzzy_infer) -> new, marketable capabilities in our hotel modelling product (https://github.com/brighterplanet/lodging/blob/master/lib/lo...).
In What it takes to build great machine learning products