Description Usage Arguments Value Examples
Decision Forest algorithm: Model training with Cross-validation Default is 5-fold cross-validation
1 2 3 4 5 6 | DFp1_CV(X, Y, CV_fold = 5, stop_step = 4, param_T = 20, param_R = 5,
param_L = 3, cp = 0.1, Filter = F, p_val = 0.05, Method = "bACC",
Quiet = T, Grace_ACC = 0.05, imp_ACC_accu = 0.01, Grace_bACC = 0.05,
imp_bACC_accu = 0.01, Grace_MCC = 0.05, imp_MCC_accu = 0.01,
Grace_MIS = ceiling(0.05 * length(Y)), imp_MIS_accu = ceiling(0.01 *
length(Y)))
|
X |
Training Dataset |
Y |
Training data endpoint |
CV_fold |
Fold of cross-validation (Default = 5) |
stop_step |
How many extra step would be processed when performance not improved, 1 means one extra step |
param_T |
Parameter T in IDF: Maximum tree number in Forest |
param_R |
parameter R in IDF: maximum occurrence of features |
param_L |
parameter L in IDF: minimum leaves in tree nodes |
cp |
parameters to pruning decision tree, default is 0.1 |
Filter |
doing feature selection before training |
p_val |
P-value threshold measured by t-test used in feature selection, default is 0.05 |
Method |
Which is used for evaluating training process. MIS: Misclassification rate; ACC: accuracy |
Quiet |
if TRUE (default), don't show any message during the process |
Grace_ACC |
Grace Value in evaluation: the next model should have a performance (Accuracy) not bad than previous model with threshold |
imp_ACC_accu |
improvement in evaluation: adding new tree should improve the overall model performance (accuracy) by threshold |
Grace_bACC |
Grace Value in evaluation: (Balanced Accuracy) |
imp_bACC_accu |
improvement in evaluation: (Balanced Accuracy) |
Grace_MCC |
Grace Value in evaluation: (MCC) |
imp_MCC_accu |
improvement in evaluation: (MCC) |
Grace_MIS |
Grace Value in evaluation: (MIS) |
imp_MIS_accu |
improvement in evaluation: (MIS) |
.$accuracy: Overall training accuracy (Cross-validation)
.$pred: Detailed training prediction (Cross-validation)
.$detail: Detailed usage of Decision tree Features/Models and their performances in all CVs
1 2 3 4 5 6 7 8 9 10 11 12 |
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