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SPSS command: SPSS ADP

Automated data preparation (ADP) in your browser

Automated data preparation recommends how to clean and transform fields before modeling.

Run Automated Data Preparation (ADP) in your browserAll SPSS procedures

Free · No account · Files stay on your device · Updated 18 October 2026

What it tells you

Crosstabs runs the SPSS ADP algorithms on your device as a preview: it never changes your data, but shows every recommended transformation and lets you download the transformed fields.

  • Which fields to drop: too many missing values, constant, dominated by one category, or unrelated to the target.
  • How outliers, missing values and measurement levels are handled for each field.
  • Which categories to merge and where to bin continuous fields against a nominal target.
  • The Box-Cox transformation of a continuous target and the predictive power of each prepared field.

When to use it

Use it when

  • Before building a regression, tree or neural network on a messy survey or customer file.
  • To see quickly which candidate predictors carry signal for a target.

Use something else when

  • You need an ordinal target or date and time handling: these parts of SPSS ADP are not included.
  • You need survey sampling weights: only frequency weights are supported.

How to run it in Crosstabs

  1. 01

    Open your data

    Open a .sav, CSV or Excel file in the workspace and switch to Statistics mode. The file is read in your browser and never uploaded.

  2. 02

    Choose Automated data preparation

    In the Machine learning group, pick Automated data preparation (ADP).

  3. 03

    Pick the target and fields

    Optionally choose a Target and its measurement level (continuous or nominal), then tick the Fields to prepare.

  4. 04

    Choose the settings

    Set how outliers are handled and how continuous fields are rescaled, and tick recasting, missing-value replacement, Box-Cox, merging, field exclusion, binning and feature construction.

  5. 05

    Run and download

    Click Run, review the recommended transformations, and download the data with the transformed fields added as CSV.

Run Automated Data Preparation (ADP) in your browser

Output tables explained

Recommended Transformations
Every kept field with its measurement level, the actions applied and the output field name.
Excluded Fields
Fields dropped by screening or selection, with the reason and p-value.
Predictive Power
r², 1 − SS within / SS total, or Cramér's V of each prepared and original field against the target.

Assumptions and notes

  • Outliers are values more than three robust standard deviations from a robust mean estimated with at most 5% of cases trimmed.
  • The workspace data are never changed; transformed fields are only offered as a download.

How the results are validated

An independent NumPy/SciPy implementation of the ADP chapter, cross-checked with SciPy f_oneway, chi2_contingency and boxcox_llf, reproduces screening, recasting, outlier bounds, replacements, merges, Scheffé cut points, constructed features, transformed values and predictive power within 1e-9 for continuous, nominal and no target, with and without frequency weights. Validation evidence

Questions

Does ADP change my data?

No. It is a preview: the recommended transformations are shown and the transformed fields can be downloaded, but the workspace data stay as they were.

What does Box-Cox do to the target?

It searches λ from −3 to 3 in steps of 0.5 for the transformation of (y − min + 1) with the highest normal log-likelihood, then rescales to mean 0 and standard deviation 1.

How are categories merged?

With a target, the pair of categories with the largest p-value is merged while p exceeds 0.05 (F tests for a continuous target, chi-square for a nominal one); without a target, sparse categories are merged by count.

What is a constructed feature?

When feature construction is on, groups of highly correlated continuous fields are replaced by their first principal component.

Related procedures

Run Automated Data Preparation (ADP) on your own data

Open a .sav, CSV or Excel file. Everything runs in your browser; the file never leaves your device.

Open the workspace

SPSS is a trademark of IBM Corp. Crosstabs is not affiliated with or endorsed by IBM.