Man pages for Beuleup93/dgrGlm
Regression logistic binary tools
| binary_predict | Binary prediction |
| centering.red.pred | centering and reduction of the test set |
| centering.reduction | centering and reduction |
| decoupage_colonne | Column Decoupage |
| decoupage_ligne | Algorithm to cut data |
| dg_batch_minibatch_online_seq | Global Gradient descent algorithm |
| dg_batch_seq | Gradient descent algorithm |
| dgrglm.fit | Function fit to construct model |
| dgrglm.multiclass.fit | Logistic regression multiclass |
| dgrglm.multiclass.predict | Binary or probabilities prediction |
| dgrglm.predict | Binary or probabilities prediction |
| dgs_minibatch_online_parallle | Batch Mini & Online DGSRow Distributed |
| dgsrow_batch_parallele | Batch DGSRow Distributed |
| dgsrow_minibatch_parallle2 | MiniBatch DGSRow Distributed |
| gradient | The gradient of the objective function |
| gradientElasticnet | Gradient for Elasticnet Loss Function |
| logLoss | Logistic regression cost function |
| logLossElasticnet | Title |
| metric_R2 | coefficient of determination R2 |
| metrics | Metrics Function |
| print.modele | Customization function of the print method for the model... |
| print.predict | Customization function of the print method for the predict... |
| recodage.quali | Recoding target variable |
| recodage_X | Re-coding Features |
| sigmoid | Sigmoid Function |
| summary.modele | Customization function of the summary method for the modele... |
| summary.predict | Customization function of the summary method for the predict... |
| var.selection | Features Selection |
