feature (gene) selection methodssample classification methods gene filtering: variance (sd/mean)...
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Feature (Gene) Selection Methods Sample Classification Methods
Gene filtering:
• Variance (SD/Mean)• Principal Component Analysis
Regression using variable selection:
•LASSO•Ridge regression•Elastic net shrinkage•Greedy algorithm
Support Vector Machines (Vapnik V, et al.)
Nearest Shrunken Centroids (Tibshirani R, et al)
Other methods:
• Decision Tree: Random Forest, CART
• k-Nearest-Neighbor• Discriminant Analysis: LDA,
DLDA• Naive Bayesian classifiers:
BART, Markov Chain Monte Carlo
• Artificial Neural Networks
•Ensemble learning: Bootstrap Aggregating, Boosting
1Supplemental File 1, Table 1s
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Supplemental File 2, Figure 2s
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Supplemental File 3, Table 2s
Type
Patients in each class CR modeling performance
CR No CR Sensitivity Specificity
Sustained CR. 36 58 53% 81%
CR3: At the end of 3rd cycle (early-onset
or flash-point CR)12 270 ~0% ~100%
CR8: At the end of 8th cycle 36 246 30% 77%
CR20: At the end of protocol 76 206 22% 81%