Man pages for Laurae2/LauraeDS
Laurae's Data Science Package
| kfold | (Un)Stratified k-fold for any type of label |
| Laurae.lgb.dmat | LightGBM Dataset generation |
| Laurae.xgb.dmat | xgboost DMatrix generation |
| Laurae.xgb.train | xgboost Model Trainer |
| lgb.wrap.loss | LightGBM loss function wrapper |
| lgb.wrap.metric | LightGBM evaluation metric wrapper |
| metrics.acc.max | Maximum binary accuracy |
| metrics.f1.max | Maximum F1 Score (Precision with Sensitivity harmonic mean) |
| metrics.fallout.max | Minimum Fall-Out (False Positive Rate) |
| metrics.kappa.max | Maximum Kappa statistic |
| metrics.logloss | Logarithmic Loss (logloss) |
| metrics.logloss.solve | Logarithmic Loss Solver |
| metrics.logloss.unsafe | Logarithmic Loss (logloss) |
| metrics.mcc.max | Maximum Matthews Correlation Coefficient |
| metrics.missrate.max | Minimum Miss-Rate (False Negative Rate) |
| metrics.precision.max | Maximum Precision (Positive Predictive Value) |
| metrics.sensitivity.max | Maximum Sensitivity (True Positive Rate) |
| metrics.specificity.max | Maximum Specificity (True Negative Rate) |
| nkfold | (Un)Stratified Repeated k-fold for any type of label |
| parallel.csv | Parallel CSV Converter |
| parallel.destroy | Parallel Destruction |
| parallel.threading | Parallel Threading Affinity Optimization |
| sparse.read | SVMLight file reader |
| sparse.write | SVMLight file writer |
| xgb.wrap.loss | xgboost loss function wrapper |
| xgb.wrap.metric | xgboost evaluation metric wrapper |
