scikit-learn-intelex
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Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
[](https://renovatebot.com) This PR contains the following updates: | Package | Change | Age | Adoption | Passing | Confidence | |---|---|---|---|---|---| | [ipython](https://ipython.org) ([source](https://togithub.com/ipython/ipython)) | `==7.29.0` -> `==7.31.1` |...
Hey there! First, fabulous work on speeding up Sklearn! I'm the author of Hyperlearn (https://github.com/danielhanchen/hyperlearn), where I also tried investigating how to speed up algos on the CPU (all the...
In both the documentation [homepage](https://intel.github.io/scikit-learn-intelex/#usage) and the global patching [page ](https://intel.github.io/scikit-learn-intelex/global-patching.html#global-patching) it is written that the command to install the global patch is `python sklearnex.glob patch_sklearn`. However, this leads to...
**Describe the bug** Cannot install newest version through pip. Prior versions are available. **To Reproduce** pip install scikit-learn-intelex==2021.6.0 **Expected behavior** Expecting to install v6.0, **Output/Screenshots**  **Environment:** Pip is up...
**Describe the bug** When I try to build the current github repo from source in anaconda I get this error in my notebook: cannot import name '_num_samples' from 'onedal.datatypes' when...
**Describe the bug** When I use train_test_split the indeces are shuffled sometimes, sometimes not. Also if you use the scoring method of an SVR estimator multiple times in a row...
Multinomial multi classes were erroring with unhandled exceptions for logistic_path because n_classes hadn't been assigned. This patch fixes the issue. # Description This is a one-liner to set the n_classes...
Hi, We are planning to integrate scikit-learn-intelex project with [PyCaret](https://www.github.com/pycaret/pycaret) The issue is as following: ``` from pycaret.datasets import get_data data = get_data('poker') from pycaret.classification import * s = setup(data,...
Add LocalOutlierFactor implementation