TimeseriesClassification | Comparing Traditional and Deep Learning techniques

by anurag1paul Jupyter Notebook Version: Current License: MIT

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

kandi X-RAY | TimeseriesClassification Summary

TimeseriesClassification is a Jupyter Notebook library. TimeseriesClassification has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Comparing Traditional and Deep Learning techniques for Multi-variate time-series classification

Support

Quality

Security

License

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Support

TimeseriesClassification has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

TimeseriesClassification has no issues reported. There are 11 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of TimeseriesClassification is current.

Quality

TimeseriesClassification has no bugs reported.

Security

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

License

TimeseriesClassification is licensed under the MIT License. This license is Permissive.

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

Reuse

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

Installation instructions are available. Examples and code snippets are not available.

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TimeseriesClassification Key Features

No Key Features are available at this moment for TimeseriesClassification.

TimeseriesClassification Examples and Code Snippets

No Code Snippets are available at this moment for TimeseriesClassification.

Community Discussions

No Community Discussions are available at this moment for TimeseriesClassification.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install TimeseriesClassification

pip install -r requirements.txt
open the Project.ipynb, set the dataset variable and run the notebook
preprocessing.py -> creates train and test dataset from the given excel file
data_loader.py -> loads and normalises the dataset
models.py -> contains classes for various classification models
select_features.py -> another file for runnning the feature selection as a subprocess
utils.py - contains functions for plotting analysis
Project.ipynb -> used for training and evaluating models

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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