How to use FVDML_TRAIN - Train Model

SAP Transaction Code - Details

• Transaction Code: FVDML_TRAIN

  Description: Train Model

  Release: S/4HANA only

  Menu Path:

  • Accounting > Bank Applications > Loans Management > Environment > Intelligent Loans Management > Train Model

• • Program: RFVD_ML_GENERATE

    Screen: 100

    Authorization Object: F_DAR_ML

  • Development Package: FVVD_ML

    Package Description: CML: Machine Learning

    Parent Package: FS_LOANS

  • Module/Component: FS-CML

    Description: Loans Management

Smart SAP Assistant

• SAP Tcode: FVDML_TRAIN - Train Model

  
  Overview:
  The SAP transaction code FVDML_TRAIN is used to train a model in the SAP system. This model can be used to predict future outcomes based on past data. The model is created using the SAP HANA Predictive Analysis Library (PAL). 
  
  Functionality: 
  The FVDML_TRAIN transaction code allows users to create a predictive model using the PAL library. This model can be used to predict future outcomes based on past data. The model can be used for various purposes, such as forecasting sales, predicting customer behavior, and more. 
  
  Step-by-Step How to Use 
  To use the FVDML_TRAIN transaction code, follow these steps 
  1. Log into the SAP system and enter the transaction code FVDML_TRAIN. 
  2. Select the type of model you want to create (e.g., linear regression, logistic regression, etc.). 
  3. Enter the data you want to use for training the model. 
  4. Select the parameters for the model (e.g., learning rate, regularization, etc.). 
  5. Train the model by clicking “Train”. 
  6. Once the training is complete, you can view the results of the model and make adjustments as needed. 
  
  Other Recommendations: 
  It is important to note that training a model requires a significant amount of time and resources. Therefore, it is recommended that users only train models when necessary and use existing models when possible. Additionally, it is important to ensure that the data used for training is accurate and up-to-date in order to get accurate results from the model.