v.3.1
Minor Release
This release adds on to the predictive analytics functionality for Qlik.
This release includes:
- Supervised Machine Learning : Implemented using scikit-learn, the go-to machine learning library for Python. This SSE implements the full machine learning flow from data preparation, model training and evaluation, to making predictions in Qlik.
- Clustering : Implemented using HDBSCAN, a high performance algorithm that is great for exploratory data analysis.
- Time series forecasting : Implemented using Facebook Prophet, a modern library for easily generating good quality forecasts.
- Seasonality and holiday analysis : Also using Facebook Prophet.
- Linear correlations : Implemented using Pandas.
Change Log v.3.1:
- Added parameter tuning functionality for supervised machine learning.
- Added a sample app for parameter tuning.
This zip archive only contains the files needed to deploy the SSE. To get the sample apps download the full source code above or get them from the docs.