| ADADELTA | ADADELTA Method Learning Function |
| ADAGRAD | ADAGRAD Method Learning Function |
| ADAM | ADADELTA Method Learning Function |
| AGD | Accelerated Gradient Descent (AGD) Method Learning Function |
| GD | Gradient Descent (GD) Method Learning Function |
| gradDescentR.learn | GradDescent Learning Function |
| gradDescentRData | Data set of the package |
| MBGD | Mini-Batch Gradient Descent (MBGD) Method Learning Function |
| MGD | Momentum Gradient Descent (MGD) Method Learning Function |
| minmaxDescaling | Min-Max Scaling Revert Function |
| minmaxScaling | The Min-Max Feature Scaling Function |
| predict | The gradDescentR prediction stage |
| predict.gradDescentRObject | The gradDescentR prediction stage |
| prediction | Predicting Function for Linear Model |
| RMSE | RMSE Calculator Function |
| RMSPROP | ADADELTA Method Learning Function |
| SAGD | Stochastic Average Gradient Descent (SAGD) Method Learning Function |
| SARAH | Stochastic Recursive Gradient Algorithm (SARAH) Method Learning Function |
| SARAHPlus | Stochastic Recursive Gradient Algorithm+ (SARAH+) Method Learning Function |
| SGD | Stochastic Gradient Descent (SGD) Method Learning Function |
| splitData | The Data Spliting Function |
| SSGD | Semi Stochastic Gradient Descent (SSGD) Method Learning Function |
| SVRG | Stochastic Variance Reduce Gradient (SVRG) Method Learning Function |
| varianceDescaling | Variance/Standardization Revert Function |
| varianceScaling | The Variance/Standardization Feature Scaling Function |