The Predict Class module will predict a new dataset based on previously stored classifier (from the Classification command). A "Prediction table" is generated that shows the prediction of the classifications of the new dataset.
To run this module, type MicroArray | Predict | Predict Class.
Input Data Requirements
It works on -Omic data types.
- Project & Data: The window includes a dropdown box to select the Project and Data object to be filtered.
- Variables: Selections can be made on which variables should be included in the filtering (options include All variables, Selected variables, Visible variables, and Customized variables (select any pre-generated Lists)).
- Observations: Selections can be made on which observations should be included in the filtering (options include All observations, Selected observations, Visible observations, and Customized observations (select any pre-generated Lists).
- Output name: The user can choose to name the output data object.
- Specify Model File: This is where the user would select a previously generated model file to be used for prediction of the new dataset in Classification.
- Observation normalization: Specify the observation normalization method for the new data.
- If the user previously used Observation normalization when doing the classification, this should be set the same here as well
- "None", "Center", and "CenterScale" are the available normalization methods
- Normalize against all variables: Checking this box will normalize the observation using all the variables in the new dataset (instead of just the variables chosen in the Variables section).
A predicted table is generated, including Design Table information from the dataset: