tpot
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EpistasisLab
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
When i try TPOT classifer while fitting to my model in colab ram became crashed on every time !! why ??
Tpot is an excellent project for beginners to get started quickly. However, I encountered some problems when I explored the features importance_ in classification tasks after I output the pipline....
I see that after the TPOT optimization a preprocessor like robustScaler was selected. I wonder if it's possible that robustScaler is applied not on the entire set of features but...
All the posts I have seen about multi-label classification are pretty old so I was wondering if TPOT currently supports it. Regards.
Hello, is it possible with TPOT to: 1. make sure that the final estimator of a pipeline is a gradientboostingregressor 2. make sure that the final estimator uses, as stacked...
I was wondering how possible it would be to incorporate the sampling preprocessors in Imbalanced learn? [https://github.com/scikit-learn-contrib/imbalanced-learn ](https://github.com/scikit-learn-contrib/imbalanced-learn) I have had a cast around the tpot code but unfortunately can't...
Is it the following behaviour expected? I start tpot with a fixed template "Selector-Transformer-Regressor" but then I get a StackingEstimator model. I am not completely sure, but I think I...
ipywidgets package should be included in the requirements.txt file. I installed tpot with conda using the documentation here http://epistasislab.github.io/tpot/installing/ and tried to run the classifier example but it failed due...
The following text is more of a feature request than a bug report. I have been using Flask to create a web app before trying TPOT. Flask requires a pickle...
Having trouble adding classifier metric + question on which metric should be used from existing ones
I'm trying to add a couple of binary classification metrics for TPOT. I have a small dataset and a binary classification problem with one class being 40% more than the...
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A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.