plot_km: Plots a series of population Kaplan-Meier curves for...
In spect: Survival Prediction Ensemble Classification Tool
plot_km R Documentation
Plots a series of population Kaplan-Meier curves for different thresholds for both
the test predictions and the ground truth
Description
Plots a series of population Kaplan-Meier curves for different thresholds for both
the test predictions and the ground truth
Usage
plot_km(train_result, prediction_threshold_search_granularity = 0.05)
Arguments
train_result
return data object from 'spect_train'
prediction_threshold_search_granularity
optional number between zero and one
which defines the granularity of searching for cumulative probability thresholds.
For instance, search a value of 0.05 will search 19 thresholds (0.05, 0.10, ..., 0.95)
Value
Data used to produce the KM curve and the passed granularity parameter. Also
plots the KM curves.
Author(s)
Stephen Abrams, stephen.abrams@louisville.edu
spect documentation built on April 11, 2025, 6:17 p.m.
R Package Documentation
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| plot_km | R Documentation |
Plots a series of population Kaplan-Meier curves for different thresholds for both the test predictions and the ground truth
Description
Plots a series of population Kaplan-Meier curves for different thresholds for both the test predictions and the ground truth
Usage
plot_km(train_result, prediction_threshold_search_granularity = 0.05)
Arguments
train_result |
return data object from 'spect_train' |
prediction_threshold_search_granularity |
optional number between zero and one which defines the granularity of searching for cumulative probability thresholds. For instance, search a value of 0.05 will search 19 thresholds (0.05, 0.10, ..., 0.95) |
Value
Data used to produce the KM curve and the passed granularity parameter. Also plots the KM curves.
Author(s)
Stephen Abrams, stephen.abrams@louisville.edu
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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