stream-outlier | Anomaly detection for multiple data streams | Predictive Analytics library

by yxjiang Java Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | stream-outlier Summary

stream-outlier is a Java library typically used in Analytics, Predictive Analytics, Spark applications. stream-outlier has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

Real Time Anomaly Detection Framework.

Support

Quality

Security

License

Reuse

Support

stream-outlier has a low active ecosystem.

It has 12 star(s) with 1 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

stream-outlier has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of stream-outlier is current.

Quality

stream-outlier has 0 bugs and 0 code smells.

Security

stream-outlier has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

stream-outlier code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

stream-outlier 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

stream-outlier 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.

stream-outlier saves you 1054 person hours of effort in developing the same functionality from scratch.

It has 2389 lines of code, 132 functions and 46 files.

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

Top functions reviewed by kandi - BETA

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

Executes a batch of stream scores
Bump the smallest elements in the given list
Partition single side
Identify the abnormal streams
Start the gather broker
Initialize alert broker
Calculates the scores for each observation
Calculates the minimum and maximum of the matrix
Synchronized
Performs a partition on the list
Start the Metadata gather broker
Entry point for the gather broker
Utility method to print out the scores and scores
Executes a batch of observation
Convert a message to a tuple
Convert message to JMS values
Static constructor
Initialize the broker
Update the stream
Executes the collector
Calculates the scores of the observation list
Runs the benchmark
Runs a batch of stream scores
Process the histogram
Main method for testing
Handles a new stream profile

Get all kandi verified functions for this library.

stream-outlier Key Features

No Key Features are available at this moment for stream-outlier.

stream-outlier Examples and Code Snippets

No Code Snippets are available at this moment for stream-outlier.

Community Discussions

Trending Discussions on Predictive Analytics

will TensorFlow utilize GPU for predictive Analysis?

Restructuring Pandas Dataframe for large number of columns

Display data from two json files in react native

QUESTION

will TensorFlow utilize GPU for predictive Analysis?

Asked 2020-Nov-21 at 21:35

GPU is good for parallel computing but the problem is some machine learning libraries don't utilize the GPU, unless that machine learning based on image processing or some sort of graphics processing, what if I am using machine learning for predictive Analytics? do libraries like TensorFlow utilize the GPU? or they use only CPU? or can I choose which processing unit to use? whats the deal here?

note: predictive Analysis requires no graphics processing.

...

ANSWER

Answered 2020-Nov-21 at 21:35

The short answer: yes, it will! The slightly longer answer:

The computation that happens in the GPU in any of the machine learning frameworks that support GPUs is not limited to graphical processing. For instance, if your model is a simple logistic regression, a framework such as TensorFlow will run it on the GPU if properly configured.

The advantage of GPUs for machine learning is that training big neural networks benefits greatly from the high level of parallelism that the GPUs offer.

If you want to know more about this, I'd recommend you start here or here.

some things to consider:

how much a model will benefit from running in the GPU will depend on how much it will benefit from parallel computation in general.
Deep Learning models can be applied to predictive analytics, as well as more classical machine learning models. Bear in mind that neural nets are possibly the category of models that will benefit inherently from the GPU (see links above).
Even though running models using GPUs (or even more specialised hardware) can bring benefits, I would suggest that you don't choose a framework and, especially, don't choose an algorithm based solely on the fact that it will benefit from parallelism, but rather look at how appropriate a given algorithm is for the data you have.

Source https://stackoverflow.com/questions/64948197

QUESTION

Restructuring Pandas Dataframe for large number of columns

Asked 2020-Nov-01 at 19:39

I have a pandas dataframe which is a large number of answers given by users in response to a survey and I need to re-structure it. There are up to 105 questions asked each year, but I only need maybe 20 of them.

The current structure is as below.

What I want to do is re-structure it so that the row values become column names and the answer given by the user is then the value in that column. In a picture (from Excel), what I want is the below (I know I'll need to re-name my columns, but that's fine once I can create the structure in the first place):

Is it possible to re-structure my dataframe this way? The outcome of this is to use some predictive analytics to predict a target variable, so I need to re-strcture before I can use Random Forest, kNN, and so on.

...

ANSWER

Answered 2020-Nov-01 at 19:39

You might want try pivoting your table:

Source https://stackoverflow.com/questions/64630691

QUESTION

Display data from two json files in react native

Asked 2020-May-17 at 23:55

I have js files Dashboard and Adverts. I managed to get Dashboard to list the information in one json file (advertisers), but when clicking on an advertiser I want it to navigate to a separate page that will display some data (Say title and text) from the second json file (productadverts). I can't get it to work. Below is the code for the Dashboard and next for Adverts. Then the json files

...

ANSWER

Answered 2020-May-17 at 23:55

The new object to get params in React Navigation 5 is:

Source https://stackoverflow.com/questions/61859411

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

Vulnerabilities

No vulnerabilities reported

Install stream-outlier

You can download it from GitHub.
You can use stream-outlier like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the stream-outlier component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

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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