Intelligent Sensing Toolbox for Multivariate Time Series
Intelligent Sensing Toolbox (Isensing) is a Python package that focuses on multivariate time series analysis. This toolbox includes multiple open-source machine learning algorithms and statistic calculations.
In data analytics, making sense of massive numbers of data requires machine learning to work on datasets from different multiple sources in order to generate insights. For situation where a node that generates data points of multiple features in time series, massive number of nodes will make analysis more challenging.
Isensing provides a list of algorithms that does features extraction, decomposition and anomaly detections.
Isensing is built upon Python 3. To install Isensing, make sure Python 3 and pip is installed.
pip install isensing
pandas numpy scipy sklearn statsmodels matplotlib plotly shapely
These dependencies will be installed automatically using pip.
# class AlphaHull HDR # functions outlier_detection() isensing_anomalies()
# class RobustPCA
# functions multiple_regression() fast_DTW() pearsonr_correlation()
Apache License 2.0
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size isensing-0.1.1-py3-none-any.whl (18.4 kB)||File type Wheel||Python version py3||Upload date||Hashes View hashes|