similarity_measures
tslearn
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similarity_measures | tslearn | |
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2 | 51 | |
236 | 2,780 | |
- | 1.4% | |
5.4 | 6.9 | |
5 months ago | 5 days ago | |
Jupyter Notebook | Python | |
MIT License | BSD 2-clause "Simplified" License |
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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
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What exactly is Partial Curve Mapping?
The Python Implementation can be found here: https://github.com/cjekel/similarity_measures/blob/master/similaritymeasures/similaritymeasures.py
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Anyone here use the Similaritymeasures library? Why is a 2D array required?
According to the documentation the function takes two arguments (exp_data and num_data ) for the data set, which makes sense. What doesn't make sense is:
tslearn
What are some alternatives?
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
neural_prophet - NeuralProphet: A simple forecasting package
Time-series-classification-and-clustering-with-Reservoir-Computing - Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
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
InceptionTime - InceptionTime: Finding AlexNet for Time Series Classification
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
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