orange3-timeseries | Orange add-on for analyzing visualizing | Predictive Analytics library

by biolab Python Version: 0.6.3 License: Non-SPDX

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

kandi X-RAY | orange3-timeseries Summary

orange3-timeseries is a Python library typically used in Analytics, Predictive Analytics, Neural Network applications. orange3-timeseries has no bugs, it has no vulnerabilities, it has build file available and it has low support. However orange3-timeseries has a Non-SPDX License. You can install using 'pip install orange3-timeseries' or download it from GitHub, PyPI.

[Documentation Status] Orange add-on for analyzing, visualizing, manipulating, and forecasting time series data. In order to use this package commercially, please obtain a [Highcharts] license.

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Quality

Security

License

Reuse

Support

orange3-timeseries has a low active ecosystem.

It has 43 star(s) with 39 fork(s). There are 14 watchers for this library.

There were 3 major release(s) in the last 6 months.

There are 26 open issues and 54 have been closed. On average issues are closed in 216 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of orange3-timeseries is 0.6.3

Quality

orange3-timeseries has 0 bugs and 0 code smells.

Security

orange3-timeseries has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

orange3-timeseries code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

orange3-timeseries 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

orange3-timeseries 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 are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed orange3-timeseries and discovered the below as its top functions. This is intended to give you an instant insight into orange3-timeseries implemented functionality, and help decide if they suit your requirements.

Set time series data
Set min and max values
Set the pixmap
Set the histogram
Mouse move event handler
Convert a pixel position to a range value
Return the subcontrol rect for subcontrol
Paint the slider slider
Return rect of subcontrol
Predict the model
Rebuilds the plot
Called when a segment is clicked
Rebuild the plot
Download data
Send the report
Runs the model evaluation
Compute the domain
Called when the checkbox has changed
Returns the errors for the model
Tries to find the closest pixel
Called when the interval value changes
Set the data
Fit the model
Overrides the mouse press event
Play a single step
Compute the aggregation for the data

Get all kandi verified functions for this library.

orange3-timeseries Key Features

No Key Features are available at this moment for orange3-timeseries.

orange3-timeseries Examples and Code Snippets

No Code Snippets are available at this moment for orange3-timeseries.

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 orange3-timeseries

You can install using 'pip install orange3-timeseries' or download it from GitHub, PyPI.
You can use orange3-timeseries 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 .

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