Titlebook: Artificial Intelligence and Soft Computing; 13th International C Leszek Rutkowski,Marcin Korytkowski,Jacek M. Zurad Conference proceedings

爆米花

Bagging of Instance Selection Algorithmsmpression and prediction accuracy. The examined instance selection algorithms for classification are ENN, CNN, RNG and GE and for regression are the developed by us Generalized CNN and Generalized ENN algorithms. Results of the comparative experimental study performed using different configurations

不可侵犯

ALIAS

Visualizing Random Forest with Self-Organising Maps well interpretable for human, the ensemble of trees is a black-box model. The popular technique to look inside the RF model is to visualize a RF proximity matrix obtained on data samples with Multidimensional Scaling (MDS) method. Herein, we present a novel method based on Self-Organising Maps (SO

noxious

PSA-velocity

Variants and Performances of Novel Direct Learning Algorithms for L2 Support Vector Machinesary and multiclass datasets. Direct L2 SVM avoids solving quadratic programming (QP) problem and it solves the Nonnegative Least Squares (NNLS) task instead, which, unlike the related iterative algorithms, produces an impeccably accurate results. Solutions obtained by NNLS and QP are equal but NNLS

MOAN

Evolving Parameters for a Noisy Biological System – The Impact of Alternative Approaches We use two different evolutionary approaches with the model: implicit and explicit. Our results reveal that significantly different characteristics of both efficiency and timescale emerge in the resulting evolved systems depending on the which particular approach is used.

占線

Epidural-Space

忍耐

Computer-Aided System for Automatic Classification of Suspicious Lesions in Breast Ultrasound Images method, the best de-noising technique from among several considered is selected, a new segmentation based on fuzzy logic is proposed and detection of lesions based on morphological features and texture features is considered. We also consider correlation among ultrasound images taken from different

legislate

The Classifier for Prediction of Peri-operative Complications in Cervical Cancer Treatment modeling and gene expression programming. This approach is applied to solve the prediction problem of peri-operative complications of radical hysterectomy in patients with cervical cancer. The developed classifier has the form of the set of fuzzy metarules, which are readable for the medical commun