McTwo: a two-step feature selection algorithm based on maximal information coefficient.
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Relevance popularity: A term event model based feature selection scheme for text classification.Machine learning based detection of age-related macular degeneration (AMD) and diabetic macular edema (DME) from optical coherence tomography (OCT) images.Multiple similarly-well solutions exist for biomedical feature selection and classification problems.RIFS: a randomly restarted incremental feature selection algorithm.Integration of 24 Feature Types to Accurately Detect and Predict Seizures Using Scalp EEG Signals.Identification of subtype-specific prognostic signatures using Cox models with redundant gene elimination.
P2860
McTwo: a two-step feature selection algorithm based on maximal information coefficient.
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2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
McTwo: a two-step feature selection algorithm based on maximal information coefficient.
@ast
McTwo: a two-step feature selection algorithm based on maximal information coefficient.
@en
type
label
McTwo: a two-step feature selection algorithm based on maximal information coefficient.
@ast
McTwo: a two-step feature selection algorithm based on maximal information coefficient.
@en
prefLabel
McTwo: a two-step feature selection algorithm based on maximal information coefficient.
@ast
McTwo: a two-step feature selection algorithm based on maximal information coefficient.
@en
P2093
P2860
P50
P1433
P1476
McTwo: a two-step feature selection algorithm based on maximal information coefficient.
@en
P2093
Fengfeng Zhou
Guoqin Mai
Guoqing Wang
Manli Zhou
Qinghan Meng
P2860
P2888
P356
10.1186/S12859-016-0990-0
P577
2016-03-23T00:00:00Z
P5875
P6179
1036575536