Normalization transforms the points along a dimension so that you can better see their distribution.
Articles for Machine Learning & Data Analytics
Insights are available with certain plot types to help draw attention to interesting, statistically significant regions of various graphs. These are written in plain English and are driven by the feature that is mapped to Color.
VIP has numerous embedded Machine Learning and Advanced Data Analytics routines that empower our users to obtain complex insights from their datasets in just a few clicks.
Smart Mapping is an AI-driven, proprietary Virtualitics routine that helps you understand your data more quickly.
Clustering is an unsupervised machine learning technique used to group points by similarity.
Principal Component Analysis (PCA) is a data analysis technique used for dimensionality reduction; it is frequently used when the dataset has a very large number of features.
Anomaly Detection identifies statistical outliers for combinations of features. There are two anomaly detection routines available in VIP: standard-deviation-based and threshold-based.
The Statistics panel provides the following useful statistics for the selected feature: min, max, median, average (mean), standard deviation, and sum.