ISLR-Python | Notes and implementations in Python for ISLR | Machine Learning library

by Kulbear Jupyter Notebook Version: Current License: MIT

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kandi X-RAY | ISLR-Python Summary

ISLR-Python is a Jupyter Notebook library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pandas applications. ISLR-Python has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Notes and implementations in Python for ISLR.

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Quality

Security

License

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Support

ISLR-Python has a low active ecosystem.

It has 14 star(s) with 7 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of ISLR-Python is current.

Quality

ISLR-Python has no bugs reported.

Security

ISLR-Python has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

ISLR-Python is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

ISLR-Python releases are not available. You will need to build from source code and install.

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ISLR-Python Key Features

No Key Features are available at this moment for ISLR-Python.

ISLR-Python Examples and Code Snippets

No Code Snippets are available at this moment for ISLR-Python.

Community Discussions

Trending Discussions on ISLR-Python

Order of priors in sklearn LinearDiscriminantAnalysis

QUESTION

Order of priors in sklearn LinearDiscriminantAnalysis

Asked 2021-Apr-03 at 13:33

I'm fitting a Linear Discriminant Analysis model using the stock market data (Smarket.csv) from here. I'm trying to predict Direction with columns Lag1 and Lag2. Direction has two values: Up or Down.

Here is my reproducible code and the result:

...

ANSWER

Answered 2021-Apr-03 at 13:33

Although I cannot find an explicit reference in the documentation (I'm sure there is a general one, somewhere), in such cases the classes are ordered alphabetically, ie. in your case it is ['Down', 'Up'].

You can easily verify that this is consistent with your results here; since the priors_ attribute is just passed through the priors argument, which, according to the documentation, is just the class proportions as inferred from the training data (when priors=None, like here):

Source https://stackoverflow.com/questions/66930904

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install ISLR-Python

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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