tslearn
R-Time-Series-Task-View-Supplement
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tslearn | R-Time-Series-Task-View-Supplement | |
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51 | 1 | |
2,780 | 2 | |
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6.9 | 8.2 | |
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BSD 2-clause "Simplified" License | - |
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tslearn
R-Time-Series-Task-View-Supplement
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R packages for finance
The R packages I have used most are quantmod and packages for GARCH such as rugarch and packages for vector autoregressions, listed in the Time Series task view , another task view for which I have created a supplement.
What are some alternatives?
sktime - A unified framework for machine learning with time series
timemachines - Predict time-series with one line of code.
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
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