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资源简介：
Classification Accuracies for Selected Brain Regions.
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创建时间：
2015-12-02
相关数据集
Comparison of classification performances of AD/MCI patients on ADNI cohort with hybrid MVPA feature selections.
Comparison of classification performances of AD/MCI patients on ADNI cohort with hybrid MVPA feature selections.
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Classification accuracy for various neuroimaging markers (50% of the data are used as training set and the rest 50% as test set, except for the last column, where a leave-one-out cross-validation is used).
The best results are achieved when we combine the features from the community matrix K and the asymmetry measure ρ. The accuracy of classification using SVM versus the number of edges selected from th
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Data_Sheet_4_Depression Classification Using Frequent Subgraph Mining Based on Pattern Growth of Frequent Edge in Functional Magnetic Resonance Imaging Uncertain Network.docx
The brain network structure is highly uncertain due to the noise in imaging signals and evaluation methods. Recent works have shown that uncertain brain networks could capture uncertain information wi
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The average CD vs CON LOOCV classification accuracies of OST-derived and Full Task derived neural activation patterns after regressing out the effect of participant sex from the beta weights.
The average CD vs CON LOOCV classification accuracies of OST-derived and Full Task derived neural activation patterns after regressing out the effect of participant sex from the beta weights.
NIAID Data Ecosystem70
Posterior decoding results.zip
Across(between) task and within task decoding results in posterior channels. Contains decoding accuracy of each time window for each comparison. perfacc_20210233.csv is the data file of behavioral acc
Mendeley Data2024-01-31 更新30
