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Despite two events (borderline, metastatic) with relatively few cases, standard logistic regression approaches performed similar to or better than regularized kernel-based alternatives, a finding to which the careful variable selection based on cross-validated c-index estimates will have contributed.
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That is, participants were faster to read regular words than pseudowords but slower to regularize words than pseudowords.
The prediction accuracies of L1-regularized methods was close to or slightly worse than that of L2 regularized methods.
Then, by incorporating with the idea of sparse learning [26], we can enforce the linear coefficients in Eq. 2, i.e., (mathbf{w}_{j,l_j}), to be sparse rather than directly regularize the prediction values (f_j mathbf{X}_i)), and present a second variant solution Sp-MIML.
To obtain this data, hereafter referred to as regularized, we define a stepsize of 24 hours which is reasonable given that we are modelling migratory pathways than span approximately 3 months.
While the root and pattern system is operative in the Berber family, it is less regularized there than in the Semitic languages.
Compositors were less than perfect; they often "regularized" the readings of their copy, altered punctuation in accordance with their own preferences or "house" style or because they lacked the necessary pieces of type, or made mistakes because they had to work too hurriedly.
In fact, we apply the well-developed LQP regularization to regularize the subproblems of the recently proposed strictly contractive PRSM, thus the resulting subproblems reduce to two nonlinear equation systems, which are much easier to solve than the subproblems of PRSM.
When control over news is a continuing (rather than temporary) condition, rumour becomes regularized as an essential aspect of daily life.
In addition, since the dimensionality of representative features considered in this study is considerably higher than that in previous studies, regularized estimation is conducted.
Regularization of the parameter estimates tends to produce stable regression models with smaller prediction error than those that are not regularized.
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