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alteryx
compose
Python2020–2020
alteryx / compose

compose

A machine learning tool for automated prediction engineering. It allows you to easily structure prediction problems and generate labels for supervised learning.

2Distinct people
17Mentions
0Explicit recommenders
515GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A machine learning tool for automated prediction engineering. It allows you to easily structure prediction problems and generate labels for supervised learning.

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

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 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 month17 dated mentions

Observed mentions: 2020-01-29 23:59:02 UTC to 2020-11-12 00:02:32 UTC.

024682020-01-01 00:00:00 UTC to 2020-02-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJan 20202020-02-01 00:00:00 UTC to 2020-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-03-01 00:00:00 UTC to 2020-04-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2020-04-01 00:00:00 UTC to 2020-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-05-01 00:00:00 UTC to 2020-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-06-01 00:00:00 UTC to 2020-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJun 20202020-07-01 00:00:00 UTC to 2020-08-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2020-08-01 00:00:00 UTC to 2020-09-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2020-09-01 00:00:00 UTC to 2020-10-01 00:00:00 UTC (exclusive): 8 mentions; 8 submissions, 0 comments2020-10-01 00:00:00 UTC to 2020-11-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2020-11-01 00:00:00 UTC to 2020-12-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 commentsNov 2020

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jan 20202020-01-01 00:00:00 UTC2020-02-01 00:00:00 UTC101
Feb 20202020-02-01 00:00:00 UTC2020-03-01 00:00:00 UTC000
Mar 20202020-03-01 00:00:00 UTC2020-04-01 00:00:00 UTC101
Apr 20202020-04-01 00:00:00 UTC2020-05-01 00:00:00 UTC000
May 20202020-05-01 00:00:00 UTC2020-06-01 00:00:00 UTC000
Jun 20202020-06-01 00:00:00 UTC2020-07-01 00:00:00 UTC000
Jul 20202020-07-01 00:00:00 UTC2020-08-01 00:00:00 UTC312
Aug 20202020-08-01 00:00:00 UTC2020-09-01 00:00:00 UTC110
Sep 20202020-09-01 00:00:00 UTC2020-10-01 00:00:00 UTC880
Oct 20202020-10-01 00:00:00 UTC2020-11-01 00:00:00 UTC110
Nov 20202020-11-01 00:00:00 UTC2020-12-01 00:00:00 UTC211

What Hacker News says

17 sources
If anyone is looking for an open source library in this space, I work on one called Compose (https://github.com/FeatureLabs/compose). With compose, a user defines a labeling function, and then compose scans the historical data looking for training examples to train a machine learning model. The library has evolved as we apply it to more and more real world use cases, but it is based on approach in this paper from 2016: https://dai.lids.mit.edu/wp-content/uploads/2016/08/07796929....
In Snorkel AI: Putting Data First in ML Development

Showing the 15 most recent of 17 sources. Enable JavaScript to search and browse every indexed mention.

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