similarity_measures VS tslearn

Compare similarity_measures vs tslearn and see what are their differences.

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similarity_measures tslearn
2 51
235 2,761
- 1.8%
5.4 7.2
4 months ago 9 days ago
Jupyter Notebook Python
MIT License BSD 2-clause "Simplified" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

similarity_measures

Posts with mentions or reviews of similarity_measures. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning similarity_measures yet.
Tracking mentions began in Dec 2020.

tslearn

Posts with mentions or reviews of tslearn. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning tslearn yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing similarity_measures and tslearn you can also consider the following projects:

sktime - A unified framework for machine learning with time series

sktime-dl - DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow

pytorch-forecasting - Time series forecasting with PyTorch

Time-series-classification-and-clustering-with-Reservoir-Computing - Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.

neural_prophet - NeuralProphet: A simple forecasting package

scikit-hts - Hierarchical Time Series Forecasting with a familiar API

R-Time-Series-Task-View-Supplement - R Time series packages not included in CRAN Task View: Time Series Analysis

Finance-Using-Python - This product helps to understand the stocks in visual manner and as well as it saves the record. And help to predict the data

InceptionTime - InceptionTime: Finding AlexNet for Time Series Classification

atspy - AtsPy: Automated Time Series Models in Python (by @firmai)

pretty-print-confusion-matrix - Confusion Matrix in Python: plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib

rocket - ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels