WTTE-RNN a framework for churn and time to event prediction
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Updated
Aug 7, 2020 - Python
WTTE-RNN a framework for churn and time to event prediction
Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).
A Python package for survival analysis. The most flexible survival analysis package available. SurPyval can work with arbitrary combinations of observed, censored, and truncated data. SurPyval can also fit distributions with 'offsets' with ease, for example the three parameter Weibull distribution.
Weibull Analysis Tools
An open-source and easy-to-use software for the comprehensive analysis of grain-size distributions
Reproduction of the work by Hong, Y., Meeker, W. Q., & McCalley, J. D. (2009). Prediction of remaining life of power transformers based on left truncated and right censored lifetime data. Annals of Applied Statistics, 3(2), 857-879.
"Pop-in" Analysis From Indentation Tests
Weibull Enabled Maintenance and Inspection Optimisation Tool (WEMIOT) is the ML driven decision analysis tool for selection maintenance policy based on data from a CMMS.
This project focuces on analysis of survival patients with Aids, with Python library Lifelines
Fréchet distribution cumulative distribution function (CDF).
Fréchet distribution.
Weibull distribution cumulative distribution function (CDF).
Fréchet distribution median.
Create a readable stream for generating pseudorandom numbers drawn from a Weibull distribution.
Weibull distribution quantile function.
Weibull distribution skewness.
Create an iterator for generating pseudorandom numbers drawn from a Weibull distribution.
Fréchet distribution mode.
Fréchet distribution skewness.
Weibull distribution mode.
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