<p>A: The results of 2-fold cross validations are shown for each regression method in this in this figure, Cox: Cox proportional hazards regression model, RSF: random survival forest, GPR: Gaussian process regression, Linear: linear (Lasso) regression, and RF: random forest. For Cox model and random survival forest, the time-event data was used as the training target while our ranking values were used for the other 3 regression method. The distribution of concordance index is represented by the width of the violin shape: the wider the shape, the greater the sample concentrated. The three red horizontal lines in each violin shape shows the lowest, mean, and the highest concordance for each method. B: The eleven features used and their availa...
(A)–(C) Comparison of validation-set performance for the 3 different states improved, no-change and ...
Logistic Regression (LR), LASSO regression, and RIDGE regression are standard classification techniq...
<p>Comparison of performance measures among Naïve Bayes, SVM and Random Forest methods on testing da...
Research that seeks to compare two predictive models requires a thorough statistical approach to dra...
The advancement in data acquiring technology continues to see survival data sets with many covariate...
<p>The methods are sorted by their AUC values in the ascending order.</p>a<p>results based on 5-fold...
A comparative analysis of two forest-based regression algorithms is an in-depth investigation of the...
Performance metrics of the prediction models using logistic regression and random forest methods wit...
<p>Comparison of the best results obtained for each data set over both models (Cox and RSF) and all ...
Random Forest (RF), a mostly model-free and robust machine learning method, has been successfully ap...
<p>The experiment was conducted 10 times using 10-fold cross-validation performed on the training se...
<p>ROCR of different models are plotted. The legend lists the number of features, AUC and sensitivit...
Abstract: Objective: The use of survival analysis has been proposed to compare the diagnostic perfor...
With big data becoming widely available in healthcare, machine learning algorithms such as random fo...
(A) shows discrimination (C-index) and (B) shows calibration (1 − a, where a is the area between the...
(A)–(C) Comparison of validation-set performance for the 3 different states improved, no-change and ...
Logistic Regression (LR), LASSO regression, and RIDGE regression are standard classification techniq...
<p>Comparison of performance measures among Naïve Bayes, SVM and Random Forest methods on testing da...
Research that seeks to compare two predictive models requires a thorough statistical approach to dra...
The advancement in data acquiring technology continues to see survival data sets with many covariate...
<p>The methods are sorted by their AUC values in the ascending order.</p>a<p>results based on 5-fold...
A comparative analysis of two forest-based regression algorithms is an in-depth investigation of the...
Performance metrics of the prediction models using logistic regression and random forest methods wit...
<p>Comparison of the best results obtained for each data set over both models (Cox and RSF) and all ...
Random Forest (RF), a mostly model-free and robust machine learning method, has been successfully ap...
<p>The experiment was conducted 10 times using 10-fold cross-validation performed on the training se...
<p>ROCR of different models are plotted. The legend lists the number of features, AUC and sensitivit...
Abstract: Objective: The use of survival analysis has been proposed to compare the diagnostic perfor...
With big data becoming widely available in healthcare, machine learning algorithms such as random fo...
(A) shows discrimination (C-index) and (B) shows calibration (1 − a, where a is the area between the...
(A)–(C) Comparison of validation-set performance for the 3 different states improved, no-change and ...
Logistic Regression (LR), LASSO regression, and RIDGE regression are standard classification techniq...
<p>Comparison of performance measures among Naïve Bayes, SVM and Random Forest methods on testing da...