BMC Medical Informatics and Decision Making

Table 4 Observed differences between the testing results and each language with p values from permutation tests

From: Comparison between machine learning methods for mortality prediction for sepsis patients with different social determinants

	English		Other		Spanish
	Observed difference	p_val	Observed difference	p_val	Observed difference	p_val
Ridge classifier	0.0154	0.279	− 0.0760	0.107	− 0.3422	*0.012*
Perceptron	0.0182	0.252	− 0.0916	0.053	− 0.3551	*0.004*
Passive-aggressive	0.0122	0.301	− 0.0555	0.172	− 0.2288	0.053
kNN	0.0166	0.263	− 0.0768	0.102	− 0.3063	*0.017*
Random forest	0.0037	0.409	− 0.0057	0.489	− 0.2342	*0.002*
LinearSVC_L1	0.0160	0.299	− 0.0772	0.102	− 0.3428	*0.003*
LinearSVC_L2	0.0156	0.297	− 0.0763	0.121	− 0.3424	*0.007*
SGDClassifier_L1	0.0184	0.246	− 0.0783	0.093	− 0.3347	*0.008*
SGDClassifier_L2	0.0187	0.269	− 0.0752	0.107	− 0.3396	*0.004*
SGDClassifier_EN	0.0181	0.259	− 0.0760	0.105	− 0.3283	*0.006*
MultinomialNB	0.0221	0.224	− 0.1210	*0.021*	− 0.2746	*0.031*
BernoulliNB	0.0076	0.389	− 0.0621	0.082	0.0306	0.422
Logistic regression	0.0145	0.293	− 0.0703	0.125	− 0.3173	*0.014*
SVC_rbf	0.0159	0.306	− 0.0825	0.080	− 0.3332	*0.012*
SVC_poly	0.0176	0.275	− 0.0860	0.079	− 0.3633	*0.002*
SVC_sigmoid	− 0.0030	0.454	0.0341	0.288	− 0.1814	0.089

Observe difference: observed difference in AUC when compared with the performance on the entire testing set; p_val: p-value, p values less than or equal to 0.05 were highlighted; Passive-aggressive: passive-aggressive classifier; kNN: k-Nearest Neighbors; LinearSVC_L1 or _L2: support vector machine with linear kernel coupled with L1 or L2 regularization; SGDClassifier_L1 or _L2 or _EN: stochastic gradient descent with L1 or L2 or Elastic Net regularization; MultinomialNB: Multinomial naïve Bayes; BernoulliNB: Bernoulli naïve Bayes; SVC_rbf or _poly or _sigmoid: support vector machine with rbf kernel or polynomial kernel or sigmoid kernel

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ISSN: 1472-6947

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