The model will use three important factors to help predict chronic The data set used in this tutorial is from the University of California, Irvine, and is the result of an extensive study based on hospital admissions over a period of time. This tutorial will take approximately 30 minutes to complete. Task 7: Deploy and test the model with new data. Task 5: Run the SPSS Modeler flow and explore the model details. Task 4: Add the nodes to the SPSS Modeler flow. In this tutorial, you will complete these tasks: Try a tutorial to create a model using SPSS Modeler This video provides a visual method as an alternative to following the written steps in this documentation.
#Clicky crisp viewmodel how to
Watch this video to see how to create and run an SPSS Modeler flow to train a machine learning model. Learn about other ways to build models Watch a video about creating a model using SPSS Modeler Each method has certain strengths and is best suited for particular types of problems. The methods available on the node palette allow you to derive new information from your data and to develop predictive SPSS Modeler offers a variety of modeling methods taken from machine learning, artificial intelligence, and statistics.
#Clicky crisp viewmodel software
Designed around the long-established SPSS Modeler client software and the industry-standardĬRISP-DM model it uses, the flows interface supports the entire data mining process, from data to better business results. With SPSS Modeler flows, you can quickly develop predictive models using business expertise and deploy them into business operations to improve decision making. Review the model details and save the model.Configure the nodes on the canvas, and run the flow.
Add an SPSS Modeler flow to the project.Projects are where you can collaborate with others to work with data. Your basic workflow includes these tasks: Required services Watson Studio (which includes SPSS Modeler) Read about SPSS Modeler, then watch a video and follow a tutorial that’s suitable for beginners and requires no coding. You can create, train, and deploy models using SPSS Modeler. Not to speak of the difficulties if singletons are involved.Quick start: Build a model using SPSS Modeler Quick start: Build a model using SPSS Modeler Quick start: Build a model using SPSS Modeler Is a lot nicer than var viewModel = new ViewModel( "some parameter", new ADependency( new OtherDependency(), new SomeService() ) var viewModel = _viewModelFactory.Create( "some parameter" )
Third, remove calls to new and replace them with calls to injected factories. If you inject that into your view model, you can still test it (verify that ShowWindow is called). Void ShowWindow( SomeParameter parameter ) You want to unittest your view models and that doesn't go well with opening real windows.
#Clicky crisp viewmodel code
Second, there's nothing wrong with this approach but for one minor remark: put the code that shows the window in a service. Probably, you want to show different content depending on which row you click the button in. I'd advise againt the ViewModelLocator here, because it makes it impossible to pass parameters to the new window. You can also register your custom window if you want the window needs to implement IDialogWindow containerRegistry.RegisterDialogWindow() įirst, you want the view model to be the DataContext (the Content is in fact the view). To use you inject into your ViewModel the IDialogService and call it (nameof(Views.Popup), dialogParmaters, (result)=> Then you need to register your view like this containerRegistry.RegisterDialog() here you get the parameters you passed Public void OnDialogOpened(IDialogParameters parameters) RequestClose.Invoke(new DialogResult(ButtonResult.OK)) you can also pass any parameters you want to back pass to the caller Public DelegateCommand OkCommand => new DelegateCommand(() => Use the IDialogService Introduced in Prism 7įirst the dialog view or ViewModel needs to implement the IDialogAware interface like this: class PopupViewModel : BindableBase, IDialogAware
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