SUOD | Acceleration System for Large-scare | Predictive Analytics library

by yzhao062 Python Version: Current License: BSD-2-Clause

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

kandi X-RAY | SUOD Summary

SUOD is a Python library typically used in Analytics, Predictive Analytics, Spark applications. SUOD has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. However SUOD has 2 bugs. You can download it from GitHub.

(MLSys' 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection)

Support

Quality

Security

License

Reuse

Support

SUOD has a low active ecosystem.

It has 347 star(s) with 43 fork(s). There are 16 watchers for this library.

It had no major release in the last 6 months.

There are 7 open issues and 3 have been closed. On average issues are closed in 102 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of SUOD is current.

Quality

SUOD has 2 bugs (0 blocker, 0 critical, 2 major, 0 minor) and 72 code smells.

Security

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

SUOD code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

SUOD is licensed under the BSD-2-Clause License. This license is Permissive.

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

Reuse

SUOD releases are not available. You will need to build from source code and install.

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

SUOD saves you 1143 person hours of effort in developing the same functionality from scratch.

It has 2582 lines of code, 65 functions and 30 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Builds a prediction prediction from a data file
Compute the cost function for each feature
Convert indices to one - hot matrix
Predict the label for each label
Predict probabilities for each estimator
Convert raw score to probability
Predict probabilities for training
Compute the cost predictor
Unfold a list of lists
Build a set of detections
Fit an estimator
Fits the Jacobian of the Jacobian
Compute the approximator for each model
Transform X into matrix X
Calculates the decision function for each estimator
Predict for each estimator
Returns a list of possible estimators
Fits the Jacobian transform using the given method
Calculates time cost for a given class
Calculate approximator
Perform a balanced task scheduling
Predict the model for the given data
Calculate the decision function
Calculate the probability of each estimator
This function returns a list of all estimators
Partition estimators between workers

Get all kandi verified functions for this library.

SUOD Key Features

No Key Features are available at this moment for SUOD.

SUOD Examples and Code Snippets

No Code Snippets are available at this moment for SUOD.

Community Discussions

Trending Discussions on SUOD

Java get all between eluding the tag

QUESTION

Java get all between eluding the tag

Asked 2017-Jul-13 at 20:06

I want to do a regex in JAVA that returns me all between the tag , but i want exclude the tag. I have this code:

...

ANSWER

Answered 2017-Jul-13 at 20:06

This worked for me for your input string. But again, this will not work for things like CDATA block inside HTML as suggested by dcsohl nor for many other strings as HTML is wickedly difficult to parse with Regex.

Source https://stackoverflow.com/questions/45087336

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

Vulnerabilities

No vulnerabilities reported

Install SUOD

You can download it from GitHub.
You can use SUOD 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

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 .

Find more information at: