Model performance | Receiver-operating characteristic curve | Precision-recall curve | Confusion matrix | Kaplan-Meier survival curves | Model calibration | Implementation details | Decision curve analysis | Variable importance | Model-specific methods | Permutation variable importance | SHAP summary plots | Feature effects | Partial dependence and individual conditional expectation plots | SHAP dependence plots | SHAP force plots | SHAP waterfall plots | Feature and sample similarity | References

Familiar in brief | Installing familiar | Pipeline | Supported outcomes | Running familiar | Configuring familiar | Preparing your data | Identifier columns | Outcome columns | Feature columns | Experimental designs | Warm start | Training models only | References

Configuration options | Generalised linear models | Linear models for binomial outcomes | Linear models for multinomial outcomes | Linear models for continuous outcomes | Linear models for survival outcomes | Lasso, ridge and elastic net regression | Extreme gradient boosted linear models and trees | Random forest (RFSRC) | Random forest (ranger) | Naive Bayes | k-nearest neighbours | Support vector machines | Hyperparameter optimization | Predicting run time of model | Assessing goodness of hyperparameter sets | Predicting optimisation score for new hyperparameter sets | Acquisition functions for utility of hyperparameter sets | Exploring challenger sets | Providing hyperparameters manually | Configuration options for hyperparameter optimisation | Model recalibration | References

Categorical outcomes | Area under the receiver-operating curve | Brier score | Contingency table-based metrics | Accuracy | Balanced accuracy | Balanced error rate | F1 score | False discovery rate | Informedness | Cohen's kappa | Markedness | Matthews correlation efficient | Negative predictive value | Positive predictive value | Recall | Specificity | Youden's J statistic | Regression outcomes | Explained variance | Mean absolute error | Relative absolute error | Mean log absolute error | Mean squared error | Relative squared error | Mean squared log error | Median absolute error | R2 score | Root mean square error | Root relative squared error | Root mean square log error | Survival outcomes | Concordance index | References

Configuration options | Providing parameters for variable importance computation | Overview of variable importance methods | Correlation methods | Concordance methods | CORElearn methods | Mutual information-based methods | Mutual information maximisation | Mutual information variable importance | Minimum redundancy maximum relevance | Univariate and multivariate regression methods | Univariate regression | Multivariate regression | Lasso, ridge and elastic net regression | Random forest-based methods | Permutation importance | Holdout permutation importance | Minimum depth variable selection | Impurity importance | Special methods | No variable importance | Random variable importance | Signature only | Aggregating variable importance | Notation | No rank aggregation | Mean rank aggregation | Median rank aggregation | Best rank aggregation | Worst rank aggregation | Stability rank aggregation | Exponential rank aggregation | Borda rank aggregation | Enhanced borda rank aggregation | Truncated borda rank aggregation | Truncated enhanced borda rank aggregation | References