Filter by

Tags

This template lets you identify customer segments for targeted marketing based on their past purchasing behavior in selected product categories.
Last Updated on 7:49pm Nov 02, 2018 by TIBCO Software
This template detects anomalous data points in a dataset using an autoencoder algorithm.  It features automated machine learning to facilitate use by business analysts and citizen data scientists.  The Time Series release of the template includes time series analysis and clustering of anomalies
Last Updated on 10:46am Jan 16, 2019 by TIBCO Software
Extreme Gradient Boosting or XGBoost is a supervised Machine-learning algorithm used to predict a target variable Y given a set of features – Xi
Last Updated on 8:49pm May 22, 2018 by TIBCO Software
Random Forest is an ensemble tree machine-learning algorithm.  This template employs supervised learning to determine variable importance and make predictions. It features automated machine learning to facilitate use by business analysts and citizen data scientists.
Last Updated on 8:48pm May 22, 2018 by TIBCO Software
Random forests are an ensemble decision tree machine learning method for classification and regression.
Last Updated on 8:48pm May 22, 2018 by TIBCO Software
This template lets you identify product categories that are likely to be bought by the same customers based on their past purchasing behavior.
Last Updated on 8:20am May 24, 2018 by TIBCO Software
This template lets you identify customers and product categories to target for promotional offers.
Last Updated on 7:47pm May 22, 2018 by TIBCO Software
This template is used to create a GBM machine learning model to understand the effects of predictor variables on a single response. 
Last Updated on 7:48pm May 22, 2018 by TIBCO Software
This template lets you prepare your data for the analyses used in the segmentation, affinity and propensity downstream Customer Analytics Templates.
Last Updated on 7:40pm May 22, 2018 by TIBCO Software
A/B testing refers to a number of similar marketing use cases where the goal is to compare the effect of different “treatments” on a response, such as click-through rates, orders or sales dollars. In the common marketing context, these treatments could be different web pages, different email designs, copy, or promotions.
Last Updated on 7:45pm May 22, 2018 by TIBCO Software

Haven't found what you are looking for?

Ask and answer questions of the community