After pretraining with a cross-entropy error function, CM-KLOGR retrains its parameters using the harmonic mean of the various evaluation criteria, including ...
Aiming at a higher classification performance with the solution of such problems, we propose a confusion- matrix-based kernel logistic regression (CM-KLOGR).
The concept and formulation of CM-KLOGR are presented, accompanied by the results of an exploratory experiment using an imbalanced biomedical dataset, ...
In order to achieve a better classification performance by formulation without heuristics and task dependence, we propose confusion-matrix-based kernel logistic ...
Sep 3, 2017 · I want to calculate two confusion matrix for my logistic regression using my training data and my testing data.
This paper presents the formulation of CM-KLOGR and its effectiveness through experiments that comparatively evaluated. CM-KLOGR using benchmark imbalanced ...
Sep 16, 2022 · I need help creating a confusion matrix from my model. Ive seen multiple sources use yhat or y_prediction, I thought weight was that. But nothing i do is ...
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Jun 25, 2015 · This paper presents the formulation of our proposed method and reports our empirical evaluation results. 1. Introduction. Data that are composed ...
Formulation of the kernel logistic regression based on the confusion matrix. M. Ohsaki, K. Matsuda, P. Wang, S. Katagiri, and H. Watanabe. CEC, page 2327 ...
This paper presents the formulation of CM-KLOGR and its effectiveness through experiments that comparatively evaluated CM- KLOGR using benchmark imbalanced ...