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Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python. Opensource analytics, predictive analytics over clickstream, sentiment analysis, machine learning, and Monte Carlo Markov Chain simulations framework over Pandas, Networkx and sklearn.
python
machine-learning
analytics
web-analytics
pandas
business-intelligence
segmentation
predictive-modeling
user-experience
predictive-analytics
clickstream
product-analytics
customer-segmentation
customer-journey-map
behaviour-analysis
user-trajectories-analysis
step-matrix
graph-visualizer
user-trajectories
cjm-simulation
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Updated
Sep 3, 2020 - Python
The complement function poorly handles larger graphs, making the nodes fly in all directions, causing arithmetic errors.
Steps to reproduce
Possible solutions
The fix should pretty much just involve trying out various functions that repulse/attract the nodes, since the current ones don't seem to handle long distances too well (see