Main Components

When you have a large set of columns (mainly numeric), it may be interesting to reduce them to a few columns that will well represent the variability existing in the different columns.

One method for this is Core Components. Gaio uses H2O to perform the calculations and summarize the data in a few columns. The algorithm accepts both numeric and categorical variables.

1. Configuration

To build the principal components analysis, simply click on the table you use, go to the Tasks menu and choose Principal Components .

  1. Define the table that will receive, in addition to your data, the columns with the components.

  2. Define how many components you want to be created.

  3. Define columns that you do not want to use in the analysis, such as Customer Code.

2. Results

The main components are presented in the first columns and then all the columns of the source table.

In this example, as 5 components were defined, five columns were created.

A report is being developed that will provide a diagnosis of the components created. For now, they are only generated, but it is not possible to identify what percentage of the data variability was concentrated in each component.

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