Create a CCA Model

In Slycat, we perform an analysis by ingesting data and creating a model. One type of Slycat model is Canonical Correlation Analysis (CCA), used to model relationships between a set of input and output metrics. Before creating a CCA model however, we must create a project, which is used to organize and control access to models.

Create a Project

  • With your web browser still pointed to the Slycat Projects page from the previous section, click the Create dropdown menu on the Slycat navbar, choose New Project, enter “MyProject” as the project name in the wizard that appears, and click Finish.
  • The browser switches to a separate page for the new project.

Generate a CCA Model

  • In the new model page, click the Create dropdown menu again, and choose New Remote CCA Model. Remote CCA is an analysis performed on a file retrieved from a host other than (remote to) the Slycat web server.
  • In the wizard that appears, enter “MyCCA” as the model name and click Next.
  • We are going to load a file that happens to be located on the same host as the Slycat server (“localhost”), but could be located on any host that’s reachable from the Slycat server over ssh. In the wizard, choose localhost in the Hostname dropdown and enter username slycat and password slycat, and click Next.
  • The remote file browser appears, displaying the filesystem of the host you chose in the previous step. Navigate to the /home/slycat/src/slycat/data directory, then double-click cars.csv. This file contains data describing 406 different types of automobile in CSV format.
  • A list of the variables (columns) from the uploaded file appears, along with two columns of checkboxes, allowing you to designate each variable as in input, an output, or neither. Use the checkboxes to select “Cylinders”, “Displacement”, “Weight”, and “Year” as inputs, and “MPG”, “Horsepower”, and “Acceleration” as outputs. Uncheck “Origin”.
  • Leave the “Scale inputs to unit variance.” checkbox checked, and click Finish.

Wait for Model Completion

The time to compute models can vary from seconds to hours, depending on the complexity of the model and the data. For this reason, Slycat computes models in the background, allowing you to:

  • Continue interacting with existing projects and models.
  • Create more than one model at a time.

This example is very small, so it should complete in a few seconds. You can jump to the new model by clicking the “You can check on it here” link in the final page of the wizard. Or, you can close the wizard, and you will see the new MyCCA model listed on the project page, where you can click on it to open it.

View a CCA Model

  • The bottom half of the model page features a table containing the raw data used to compute the model. Input variables are color-coded green, output variables are color-coded purple, and unused variables are color-coded white.
  • The upper-left corner of the page contains the CCA table, a high-level overview of the CCA results including statistical significance measures and bar-plots for each input and output variable over three CCA components.
  • The upper-right corner of the page contains a scatterplot detailing how well each individual observation in the raw data fits the currently selected CCA component.

Interact with a CCA Model

  • Click a component name (“CCA1”, “CCA2”, or “CCA3”) in the CCA table to select that component, displaying its bar plot and updating the scatterplot.
  • Click variable names in the CCA table or the raw data table to color code observations with that variable.
  • Hover over columns in the CCA table and the raw data table to reveal sorting widgets.
  • Click observations in the scatterplot to highlight the corresponding entry in the raw data table.
  • Click and drag in the scatterplot to rubber-band-select multiple observations.
  • Click rows or shift-click ranges of rows in the raw data table to highlight corresponding observations in the scatterplot.

Next Steps

Now that you’ve created your first CCA model it’s time to Create a Timeseries Model.