LogisticRegression | Logistic Regression
kandi X-RAY | LogisticRegression Summary
Support
- LogisticRegression has a low active ecosystem.
- It has 0 star(s) with 0 fork(s). There are no watchers for this library.
- It had no major release in the last 12 months.
- LogisticRegression has no issues reported. On average issues are closed in 13 days. There are no pull requests.
- It has a neutral sentiment in the developer community.
- The latest version of LogisticRegression is current.
Quality
- LogisticRegression has no bugs reported.
Security
- LogisticRegression has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
- LogisticRegression does not have a standard license declared.
- Check the repository for any license declaration and review the terms closely.
- Without a license, all rights are reserved, and you cannot use the library in your applications.
Reuse
- LogisticRegression releases are not available. You will need to build from source code and install.
- LogisticRegression has no build file. You will be need to create the build yourself to build the component from source.
Coming Soon for all Libraries!
Currently covering the most popular Java, JavaScript and Python libraries. See a SAMPLE HERE.
kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
LogisticRegression Key Features
Logistic Regression is a Machine Learning classification algorithm that is used to predict the probability of a categorical dependent variable. In logistic regression, the dependent variable is a binary variable that contains data coded as 1 or 0
LogisticRegression Examples and Code Snippets
No Code Snippets are available at this moment for LogisticRegression.Refer to component home page for details.
No Code Snippets are available at this moment for LogisticRegression.Refer to component home page for details.
Community Discussions
No Community Discussions are available at this moment for LogisticRegression.Refer to stack overflow page for discussions.
No Community Discussions are available at this moment for LogisticRegression.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install LogisticRegression
You can use LogisticRegression like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
Reuse Trending Solutions
Reuse Solution Kits and Libraries Curated by Popular Use Cases
Save this library and start creating your kit