AIMC Topic: Datasets as Topic

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A fuzzy integral method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification across multiple subjects.

Journal of integrative neuroscience
The huge number of voxels in fMRI over time poses a major challenge to for effective analysis. Fast, accurate, and reliable classifiers are required for estimating the decoding accuracy of brain activities. Although machine-learning classifiers seem ...

SVM and SVM Ensembles in Breast Cancer Prediction.

PloS one
Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among...

Nano Random Forests to mine protein complexes and their relationships in quantitative proteomics data.

Molecular biology of the cell
Ever-increasing numbers of quantitative proteomics data sets constitute an underexploited resource for investigating protein function. Multiprotein complexes often follow consistent trends in these experiments, which could provide insights about thei...

A L1-regularized feature selection method for local dimension reduction on microarray data.

Computational biology and chemistry
Dimension reduction is a crucial technique in machine learning and data mining, which is widely used in areas of medicine, bioinformatics and genetics. In this paper, we propose a two-stage local dimension reduction approach for classification on mic...

A new model of flavonoids affinity towards P-glycoprotein: genetic algorithm-support vector machine with features selected by a modified particle swarm optimization algorithm.

Archives of pharmacal research
Flavonoids exhibit a high affinity for the purified cytosolic NBD (C-terminal nucleotide-binding domain) of P-glycoprotein (P-gp). To explore the affinity of flavonoids for P-gp, quantitative structure-activity relationship (QSAR) models were develop...

Online 3D Ear Recognition by Combining Global and Local Features.

PloS one
The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for onl...

Resistance gene identification from Larimichthys crocea with machine learning techniques.

Scientific reports
The research on resistance genes (R-gene) plays a vital role in bioinformatics as it has the capability of coping with adverse changes in the external environment, which can form the corresponding resistance protein by transcription and translation. ...

A Self-Adaptive Fuzzy -Means Algorithm for Determining the Optimal Number of Clusters.

Computational intelligence and neuroscience
For the shortcoming of fuzzy -means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters. Firstly, a density-based algorithm was put forward. The...

Prediction of Protein-Protein Interactions by Evidence Combining Methods.

International journal of molecular sciences
Most cellular functions involve proteins' features based on their physical interactions with other partner proteins. Sketching a map of protein-protein interactions (PPIs) is therefore an important inception step towards understanding the basics of c...

A new hyperbox selection rule and a pruning strategy for the enhanced fuzzy min-max neural network.

Neural networks : the official journal of the International Neural Network Society
In this paper, we extend our previous work on the Enhanced Fuzzy Min-Max (EFMM) neural network by introducing a new hyperbox selection rule and a pruning strategy to reduce network complexity and improve classification performance. Specifically, a ne...