af.softmax |
An Activation Function: Softmax |
CD |
the Comparison Data (CD) Approach |
CDF |
the Comparison Data Forest (CDF) Approach |
data.bfi |
25 Personality Items Representing 5 Factors |
data.datasets |
Subset Dataset for Training the Pre-Trained Deep Neural Network (DNN) |
data.scaler |
the Scaler for the Pre-Trained Deep Neural Network (DNN) |
DNN_predictor |
A Pre-Trained Deep Neural Network (DNN) for Determining the Number of Factors |
EFAhclust |
Hierarchical Clustering for EFA |
EFAindex |
Various Indeces in EFA |
EFAkmeans |
K-means for EFA |
EFAscreet |
Scree Plot |
EFAsim.data |
Simulate Data that Conforms to the theory of Exploratory Factor Analysis. |
EFAvote |
Voting Method for Number of Factors in EFA |
EKC |
Empirical Kaiser Criterion |
extractor.feature.DNN |
Extracting features for the Pre-Trained Deep Neural Network (DNN) |
extractor.feature.FF |
Extracting features According to Goretzko & Buhner (2020) |
factor.analysis |
Factor Analysis by Principal Axis Factoring |
FF |
Factor Forest (FF) Powered by An Tuned XGBoost Model for Determining the Number of Factors |
GenData |
Simulating Data Following John Ruscio's RGenData |
Hull |
the Hull Approach |
KGC |
Kaiser-Guttman Criterion |
load_DNN |
Load the Trained Deep Neural Network (DNN) |
load_scaler |
Load the Scaler for the Pre-Trained Deep Neural Network (DNN) |
load_xgb |
Load the Tuned XGBoost Model |
model.xgb |
the Tuned XGBoost Model for Determining the Number of Facotrs |
normalizor |
Feature Normalization |
PA |
Parallel Analysis |
plot.CD |
Plot Comparison Data for Factor Analysis |
plot.CDF |
Plot Comparison Data Forest (CDF) Classification Probability Distribution |
plot.DNN_predictor |
Plot DNN Predictor Classification Probability Distribution |
plot.EFAhclust |
Plot Hierarchical Cluster Analysis Dendrogram |
plot.EFAkmeans |
Plot EFA K-means Clustering Results |
plot.EFAscreet |
Plots the Scree Plot |
plot.EFAvote |
Plot Voting Results for Number of Factors |
plot.EKC |
Plot Empirical Kaiser Criterion (EKC) Plot |
plot.FF |
Plot Factor Forest (FF) Classification Probability Distribution |
plot.Hull |
Plot Hull Plot for Factor Analysis |
plot.KGC |
Plot Kaiser-Guttman Criterion (KGC) Plot |
plot.PA |
Plot Parallel Analysis Scree Plot |
predictLearner.classif.xgboost.earlystop |
Prediction Function for the Tuned XGBoost Model with Early Stopping |
print.CD |
Print Comparison Data Method Results |
print.CDF |
Print Comparison Data Forest (CDF) Results |
print.DNN_predictor |
Print DNN Predictor Method Results |
print.EFAdata |
Print the EFAsim.data |
print.EFAhclust |
Print EFAhclust Method Results |
print.EFAkmeans |
Print EFAkmeans Method Results |
print.EFAscreet |
Print the Scree Plot |
print.EFAvote |
Print Voting Method Results |
print.EKC |
Print Empirical Kaiser Criterion Results |
print.FF |
Print Factor Forest (FF) Results |
print.Hull |
Print Hull Method Results |
print.KGC |
Print Kaiser-Guttman Criterion Results |
print.PA |
Print Parallel Analysis Method Results |