Risk calculation charts for multiclass prediction models

Risk calculation charts for multiclass prediction models

Methods Binary logistic regression models, where the estimated risk equals p=1/(1+exp(-b0-xb)) can be visualized by representing the contribution of each predictor (x_ib_i) with a colorbar, the color of which represents the value of the contribution. An additional colorbar is used to transform the sum of these contributions to a risk. For multinomial models, the linear predictors (lp_l=b0^l+xb^...

Performance Bounds for Multiclass Models

Visualizing Risk Prediction Models

OBJECTIVE Risk prediction models can assist clinicians in making decisions. To boost the uptake of these models in clinical practice, it is important that end-users understand how the model works and can efficiently communicate its results. We introduce novel methods for interpretable model visualization. METHODS The proposed visualization techniques are applied to two prediction models from ...

Logarithmic Time Online Multiclass prediction

We study the problem of multiclass classification with an extremely large numberof classes (k), with the goal of obtaining train and test time complexity logarith-mic in the number of classes. We develop top-down tree construction approachesfor constructing logarithmic depth trees. On the theoretical front, we formulate anew objective function, which is optimized at each node of...

Two criteria for evaluating risk prediction models.

We propose and study two criteria to assess the usefulness of models that predict risk of disease incidence for screening and prevention, or the usefulness of prognostic models for management following disease diagnosis. The first criterion, the proportion of cases followed PCF (q), is the proportion of individuals who will develop disease who are included in the proportion q of individuals in ...