MLJAR AutoML
AI
automl
SHOW HN2022
67points
15comments
#808of 2,570 in 2022
Top 32%of 2022 by points
How HN took it
QuietFewer than 5 comments about the project
2 positive, 1 neutral or asking, 1 mixed, 0 critical, out of 4 comments about the project.
Idea: 2 for, 0 against
The thread, comment by comment
Each row is a top-level comment and its replies, in HN's order. Select a cell to open that comment on HN.
positive neutral or mixed critical about another commenter or something else the maker
What HN said
What people liked
Useful for exploring ML on tabular data and educational
From 2 comments
This looks really great. I can imagine adding some features around the explanations from an educational standpoint. You could go from never having done this to understanding a…
chrisgd on HNSometimes I just absolutely love hacker news more than words can explain. I am knee deep in a personal project exploring machine learning on tabular data and it’s been consuming…
nlh on HN
Objections
Only tests one neural network model, not several top architectures
From 1 comment
Neat! I'll test it tomorrow. My only 'complaint' from reading the docs is that it only tests one NN model (which is the same for all types of data), rather than at least a few of…
Tenoke on HN
Gradient boosting libraries like XGBoost and LightGBM may be better without AutoML
From 2 comments
If you have tabular data just run with xgboost/lightgbm.
nojito on HNAt least for tabular data there is no clear evidence that a neural network is superior than a tree-based model [0]. Many Data Scientist colleagues go straight to neural networks…
sebastiansm on HN
Requests
Add explanations to support learning
From 1 comment
This looks really great. I can imagine adding some features around the explanations from an educational standpoint. You could go from never having done this to understanding a…
chrisgd on HN
Questions
Can XGBoost/LightGBM handle out-of-time predictions for price regression
From 1 comment
Yeah it seems those are still kings of the hill. One newbie question maybe you can answer: Can XGboost/LightGBM handle out of band data predictions? The specific regression…
nlh on HN
Alternatives named
FLAML
From 1 comment
There are many AutoML frameworks out there. For example, I recently found FLAML, which focuses on finding an optimal model given a budget. In case, you wanna check it out:…
d3nigma on HN
H2O AutoML
From 1 comment
https://h2o-release.s3.amazonaws.com/h2o/rel-zumbo/4/index.html
eyeball on HN
XGBoost and LightGBM
From 1 comment
If you have tabular data just run with xgboost/lightgbm.
nojito on HN
PyGraphistry
From 1 comment
Maybe useful: As part of improving autoML in PyGraphistry, we have been a doing a lot of auto-feature-engineering and auto-clustering work for one-liners like:…
lmeyerov on HN