The Encoding component transforms categorical text columns into numbers so ML models can work with them.
Configuration
| Option | Description |
|---|
| Method | Encoding strategy (see table below). |
| Features | Categorical columns to encode. |
Methods
| Method | How it works | Best for |
|---|
| Ordinal Encoding | Assigns an integer (0, 1, 2, …) to each category. Preserves order if categories have a natural ranking. | Ordinal categories (e.g. Low / Medium / High) |
| One Hot Encoding | Creates a new binary column for each unique category value. | Nominal categories with no inherent order (e.g. Color, City) |
| Type |
|---|
| Input | DataFrame |
| Output | DataFrame |
One Hot Encoding expands the number of columns. For columns with many unique values (high cardinality), this can make the DataFrame very wide. Consider Feature Selection afterward.
