After building a machine learning model in LityxIQ, you will likely want to analyze it. LityxIQ provides a wide variety of methods evaluating and exploring models. They are briefly explained here, with links to more detailed overviews of each.
Performance Analysis - analyze the quantitative and qualitative performance of the model, and compare models and versions against each other. See https://support.lityxiq.com/378413-Analyzing-Model-Performance for more.
Model Explorer - interactively explore the complex patterns and relationships among model variables. See https://support.lityxiq.com/150993-Using-the-Model-Explorer for more.
Threshold Analysis - interactively determine optimal cutoff values based on the cost of different kinds of prediction errors (only available for binary classification models). See https://support.lityxiq.com/784904-Threshold-Analysis-and-Error-Cost-Analysis for more.
Engagement Analysis - interactively determine optimal depth for marketing campaigns to maximize profitability (only available for binary classification models). see https://support.lityxiq.com/001495-Engagement-Analysis for more.
To get started with any of these, select the model you would like to evaluate or explore, and hover on Evaluate & Explore from the Selected Model menu or the right click menu. This will open a sub-menu with the various options.