causallift | Python package for causality-based Uplift Modeling | Machine Learning library

by Minyus Python Version: 1.0.6 License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | causallift Summary

causallift is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. causallift has no bugs, it has no vulnerabilities, it has build file available and it has low support. However causallift has a Non-SPDX License. You can install using 'pip install causallift' or download it from GitHub, PyPI.

If you are simply building a Machine Learning model and executing promotion campaigns to the customers who are predicted to buy a product, for example, it is not efficient. Some customers will buy a product anyway even without promotion campaigns (called "Sure things"). It is even possible that the campaign triggers some customers to churn (called "Do Not Disturbs" or "Sleeping Dogs"). The solution is Uplift Modeling.

Support

Quality

Security

License

Reuse

Support

causallift has a low active ecosystem.

It has 312 star(s) with 41 fork(s). There are 9 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 19 have been closed. On average issues are closed in 87 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of causallift is 1.0.6

Quality

causallift has 0 bugs and 0 code smells.

Security

causallift has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

causallift code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

causallift has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

causallift releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed causallift and discovered the below as its top functions. This is intended to give you an instant insight into causallift implemented functionality, and help decide if they suit your requirements.

Fit the density model
Fit the model
Return a pandas DataFrame with the score for each partition
Apply method to obj
Estimate the propensity score for training and test data
Concatenate train and test data
Returns the predicted probabilities for each sample
Concatenate train and test and test data
Run jupyter notebook
Prints a message to the user
Build jupyter command
Compute the gain from the given data
Returns the number of items in the given dataframe
Estimate the overall uplift gain
Impute cols_features
Return a list of columns in a dataframe
Run the pipeline
Check if missing ds are missing
Runs a Kedro cluster
Run the project
Setup the extension
Run jupyter notebook
Reload kedro project context
Extract treatment fractions from a dataframe
Combine train and test data
Launch ipython

Get all kandi verified functions for this library.

causallift Key Features

No Key Features are available at this moment for causallift.

causallift Examples and Code Snippets

No Code Snippets are available at this moment for causallift.

Community Discussions

Trending Discussions on causallift

'pip install causallift' does not install

QUESTION

'pip install causallift' does not install

Asked 2020-Jan-03 at 11:01

I want to install the Python package causallift, but the installation lingers at 'Installing build dependencies...'.

When I install with:

...

ANSWER

Answered 2020-Jan-03 at 10:36

you can try 2 more options:

run: pip3 install git+https://github.com/Minyus/causallift.git
clone the GitHub repository, cd into the downloaded repository, and run: python setup.py install

Source https://stackoverflow.com/questions/59576783

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

Vulnerabilities

No vulnerabilities reported

Install causallift

[Option 1] To install the latest release from the PyPI:
[Option 2] To install the latest pre-release:
[Option 3] To install the latest pre-release without need to reinstall even after modifying the source code: