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The Gini impurity is based on squared probabilities of membership for each target category in the node.
The Gini index is a measure based on squared probabilities of membership for each target category in the node [ 48].
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Generally, the approach based on squared semipartial correlations should be preferred above the approach based on squared betas.
Note: These measurements are based on squared dimensions.
The outputs of singular stochastic systems are described by probability density functions (PDFs) based on square root B-spline expansions.
The goodness-of-fit model was evaluated using the Pearson chi-square test and the Hosmer-Lemeshow test: Pearson chi-square 48.3 (53 degrees of freedom), probability greater than chi-square 0.66, Hosmer-Lemeshow chi-square 0.5.3 (data divided into ten groups based on the predicted probability), probability greater than chi-square 0.73.
The Hosmer and Lemeshow's (H-L) goodness of fit test divides subjects into deciles based on predicted probabilities, then computes a chi-square from observed and expected frequencies.
Calibration was assessed using the Hosmer-Lemeshow goodness of fit statistic which divides subjects into deciles based on predicted probabilities of death and then computes a chi-square from observed and expected frequencies [ 45].
Class assignment was based on posterior probabilities.
Exact CIs were calculated based on binomial probabilities.
The Hosmer-Lemeshow test (H) was used to assess the fit of the models, which divides subjects into deciles based on their predicted probabilities before computing Chi-square values from the observed and expected frequencies [ 17- 20].
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