> ## Documentation Index
> Fetch the complete documentation index at: https://docs.clickml.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Feature Transformation component

> Create new features from existing columns through polynomial expansion, binning, log transforms, and other engineered transformations.

The **Feature Transformation** component creates new features derived from selected columns. Unlike Data Transformation (which modifies values in-place), this component adds or replaces columns with newly engineered features.

## Configuration

| Option                                  | Description                                             | Default   |
| --------------------------------------- | ------------------------------------------------------- | --------- |
| **Method**                              | Transformation to apply (see table below)               | —         |
| **Columns**                             | Columns to use as input for the transformation          | —         |
| **Degree** *(Polynomial / Interaction)* | Polynomial degree                                       | `2`       |
| **N Bins** *(Binning)*                  | Number of bins                                          | `5`       |
| **Bin Strategy** *(Binning)*            | `uniform` (equal-width) or `quantile` (equal-frequency) | `uniform` |

### Methods

| Method               | What it creates                                                            |
| -------------------- | -------------------------------------------------------------------------- |
| Polynomial Features  | All polynomial combinations up to the given degree (e.g. `x`, `x²`, `x·y`) |
| Interaction Features | Only interaction terms between selected features (no pure powers)          |
| Binning              | Discretizes continuous values into `N` categorical bins                    |
| Label Encoding       | Encodes string values as integers (in-place)                               |
| Frequency Encoding   | Replaces each category with its relative frequency in the dataset          |

## Input / Output

|        | Type      |
| ------ | --------- |
| Input  | DataFrame |
| Output | DataFrame |