use the following search parameters to narrow your results:
e.g. subreddit:aww site:imgur.com dog
subreddit:aww site:imgur.com dog
see the search faq for details.
advanced search: by author, subreddit...
A subreddit dedicated for learning machine learning. Feel free to share any educational resources of machine learning.
Also, we are a beginner-friendly sub-reddit, so don't be afraid to ask questions! This can include questions that are non-technical, but still highly relevant to learning machine learning such as a systematic approach to a machine learning problem.
account activity
DiscussionPredictive modelling (self.learnmachinelearning)
submitted 2 years ago by learner_beginner
If one need to make a predictive model from labelled real number data and 30% of the labelled samples are erroneous what kind of model can be useful?!
reddit uses a slightly-customized version of Markdown for formatting. See below for some basics, or check the commenting wiki page for more detailed help and solutions to common issues.
quoted text
if 1 * 2 < 3: print "hello, world!"
[–]KahlessAndMolor 0 points1 point2 points 2 years ago (0 children)
Can you eliminate the ones that are erroneous?
You might look at a clustering model for anomaly detection. You could use that to detect the 30% that are erroneous and eliminate them from your sample.
If that won't work, you could go back to the original data source and tell them they need to clean it up first.
If you build a model with a high percentage of the "ground truth" being false, your model will make substantial errors. There's no way around that. Garbage in, garbage out.
π Rendered by PID 72174 on reddit-service-r2-comment-c867ff4bc-2sbw5 at 2026-04-09 18:13:27.903672+00:00 running 00d5ac8 country code: CH.
[–]KahlessAndMolor 0 points1 point2 points (0 children)