Journament

Keyword Connections - feature selection Keywords

Connection Type	Connection
Journals	Frontiers in plant science International journal of pharmaceutics Sensors (Basel, Switzerland) BMC Bioinformatics Frontiers in psychology Journal of environmental management neural networks : the official journal of the international neural network society Computational biology and chemistry Briefings in bioinformatics methods in molecular biology (clifton, nj) Frontiers in genetics computer methods and programs in biomedicine Computational Intelligence and Neuroscience addictive behaviors reports Frontiers in computational neuroscience bmc medical genomics human heredity Medical image analysis Metabolites journal of digital imaging pharmacoeconomics Current opinion in plant biology canadian journal of experimental psychology = revue canadienne de psychologie experimentale annual review of genomics and human genetics
Research Groups	No Research Group Connected
Bibliographies	[1] Internet addiction disorder detection of Chinese college students using several personality questionnaire data and support vector machine. [2] Predicting Post-Translational Modifications from Local Sequence Fragments Using Machine Learning Algorithms: Overview and Best Practices. [3] The metaRbolomics Toolbox in Bioconductor and beyond. [4] Cooking Up a Transparent Model Following a DICE Recipe. [5] Robustness of Radiomics for Survival Prediction of Brain Tumor Patients Depending on Resection Status. [6] Predictive Feature Generation and Selection Using Process Data From PISA Interactive Problem-Solving Items: An Application of Random Forests. [7] Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease. [8] A micro-XRT Image Analysis and Machine Learning Methodology for the Characterisation of Multi-Particulate Capsule Formulations. [9] Antimicrobial resistance genetic factor identification from whole-genome sequence data using deep feature selection. [10] A network clustering based feature selection strategy for classifying autism spectrum disorder. [11] iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data. [12] Structured pruning of recurrent neural networks through neuron selection. [13] Effet de la valence émotionnelle de textes sur leur compréhension et l'apprentissage de nouveaux mots chez des élèves de 5éme année de primaire. [14] Enhanced Human Activity Recognition Based on Smartphone Sensor Data Using Hybrid Feature Selection Model. [15] Channel Projection-Based CCA Target Identification Method for an SSVEP-Based BCI System of Quadrotor Helicopter Control. [16] A new machine learning technique for an accurate diagnosis of coronary artery disease. [17] A CNN-RNN Framework for Crop Yield Prediction. [18] Automated Cardiovascular Pathology Assessment Using Semantic Segmentation and Ensemble Learning. [19] Hellinger distance-based stable sparse feature selection for high-dimensional class-imbalanced data. [20] How to Select Balance Measures Sensitive to Parkinson’s Disease from Body-Worn Inertial Sensors—Separating the Trees from the Forest [21] Prediction of Peptide Vascularization Inhibitory Activity in Tumor Tissue as a Possible Target for Cancer Treatment [22] Prediction of Peptide Vascularization Inhibitory Activity in Tumor Tissue as a Possible Target for Cancer Treatment [23] Support Vector Machine Optimized by Genetic Algorithm for Data Analysis of Near-Infrared Spectroscopy Sensors [24] Support Vector Machine Optimized by Genetic Algorithm for Data Analysis of Near-Infrared Spectroscopy Sensors [25] plant species discrimination in a tropical wetland using in situ hyperspectral data [26] The CSP-Based New Features Plus Non-Convex Log Sparse Feature Selection for Motor Imagery EEG Classification. [27] ceai: ccm-based email authorship identification model [28] random forest method for dimension reduction and point cloud classification based on airborne lidar [29] feature selection of network intrusion data using genetic algorithm and particle swarm optimization [30] decoding subjective intensity of nociceptive pain from pre-stimulus and post-stimulus brain activities [31] Automatic Feature Selection for Imbalanced Echocardiogram Data Using Event-Based Self-Similarity. [32] Tlalpan 2020 Case Study: Enhancing Uric Acid Level Prediction with Machine Learning Regression and Cross-Feature Selection. [33] Performance Assessment of Multiple Classifiers Based on Ensemble Feature Selection Scheme for Sentiment Analysis [34] An Automated Approach for Epilepsy Detection Based on Tunable Q-Wavelet and Firefly Feature Selection Algorithm [35] A Novel Feature Selection Method for High-Dimensional Biomedical Data Based on an Improved Binary Clonal Flower Pollination Algorithm. [36] Principal Component Analysis Based on Graph Laplacian and Double Sparse Constraints for Feature Selection and Sample Clustering on Multi-View Data. [37] Data driven feature selection and machine learning to detect misplaced V1 and V2 chest electrodes when recording the 12‑lead electrocardiogram. [38] Classification-oriented fuzzy-rough feature selection for the eeg-based brain-computer interfaces [39] An instance voting approach to feature selection [40] Whale Optimization Algorithm for High-dimensional Small-Instance Feature Selection [41] Feature Selection for Financial Data Classification: Islamic Finance Application [42] PhosphoPredict: A bioinformatics tool for prediction of human kinase-specific phosphorylation substrates and sites by integrating heterogeneous feature selection. [43] Hybrid binary particle swarm optimization and flower pollination algorithm based on rough set approach for feature selection problem [44] Integrating joint feature selection into subspace learning: A formulation of 2DPCA for outliers robust feature selection. [45] Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease. [46] Antimicrobial resistance genetic factor identification from whole-genome sequence data using deep feature selection. [47] A network clustering based feature selection strategy for classifying autism spectrum disorder. [48] Enhanced Human Activity Recognition Based on Smartphone Sensor Data Using Hybrid Feature Selection Model. [49] Feature selection for helpfulness prediction of online product reviews: An empirical study. [50] EMG Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization [51] Discrete particle swarm optimization based filter feature selection technique for the severity of road traffic accident prediction [52] Correlation-based feature selection for resilience analysis of MVDC shipboard power system [53] Developing a deep learning framework with two-stage feature selection for multivariate financial time series forecasting [54] Hellinger distance-based stable sparse feature selection for high-dimensional class-imbalanced data. [55] Feature selection and classification by minimizing overlap degree for class-imbalanced data in metabolomics [56] Simultaneous feature selection and heterogeneity control for SVM classification: An application to mental workload assessment [57] predicting presynaptic and postsynaptic neurotoxins by developing feature selection technique [58] intrusion detection model using fusion of chi-square feature selection and multi class svm [59] residential electricity consumption level impact factor analysis based on wrapper feature selection and multinomial logistic regression [60] feature selection and parameters optimization of svm using particle swarm optimization for fault classification in power distribution systems [61] diagnosing autism spectrum disorder from brain resting-state functional connectivity patterns using a deep neural network with a novel feature selection method [62] The CSP-Based New Features Plus Non-Convex Log Sparse Feature Selection for Motor Imagery EEG Classification. [63] effective feature selection for 5g im applications traffic classification [64] pathway-based feature selection algorithm for cancer microarray data [65] a novel feature selection strategy for enhanced biomedical event extraction using the turku system [66] feature selection of network intrusion data using genetic algorithm and particle swarm optimization [67] an active feature selection strategy for dwt in artificial taste [68] feature selection and parameter optimization of support vector machines based on modified artificial fish swarm algorithms [69] Machine Learning Feature Selection Methods for Landslide Susceptibility Mapping [70] Feature selection using binary cuckoo search algorithm [71] Impact of Feature Selection Algorithm on Speech Emotion Recognition Using Deep Convolutional Neural Network [72] Automatic Feature Selection for Imbalanced Echocardiogram Data Using Event-Based Self-Similarity. [73] Tlalpan 2020 Case Study: Enhancing Uric Acid Level Prediction with Machine Learning Regression and Cross-Feature Selection.