Dataset features

The dataset’s features are the columns in the dataset matrix. The features are used in the Input or Target block in the Modeling view.

Above each feature, you can see the feature distribution as well as the label and shape.

If you select a feature you can change the label, the feature encoding, e.g., from numeric to categorical, and whether and how it should be normalized.

Feature set

A feature set consists of features that you want to group for use in the Input or Target block (it is possible to create a feature set with only one feature, but then it’s much simpler to use the feature as it is).
The feature sets are shown above the dataset features in the Dataset view.

If you select a feature set only the included features will be shown in the Datasets view.

Compatible dimensions
You can only combine features with compatible dimensions. This means all dimensions except one must be the same. For instance, you cannot create a feature set that includes 28x28x1 pixel images and scalar values, but you can combine 28x28x1 monochrome images with 28x28x3 RGB images.

Features and feature sets on the Peltarion Platform
Figure 1. Features and feature sets on the Peltarion Platform.

Example: We want to build a model that predicts the price of a house. Your training data consists of an image of a house and some numeric values about the house including its sale price. Then you should, as an input feature, create a feature set with all tabular features, excluding the price.
You can do exactly this in the tutorial "Predict California house prices".

How to create a feature set

  1. Click New feature set.

  2. In the Edit feature set pop-up, select the features you want to combine.
    You can only combine features with the compatible dimensions.

  3. If you need to, change the order of the features.

  4. Name the new feature set.

  5. Click Create.

Change order of features in a feature set

In most cases, the order of the features in a feature set is not relevant. The only time the order is relevant is when you want to reuse a pretrained model that was trained on features in a specific order.

Example: You want to use a model that has been trained on a feature set consisting of age, height, and weight (in this order). The new feature set you create for the new model must then use the same order. Otherwise, someone that is 185 cm tall and weighs 80 kg may be interpreted as 80 cm tall and 185 kg heavy, that is, considerably shorter and fatter.

The order of the features is shown in the Selected features section in the Edit feature set pop-up. This pop-up opens when you create or edit a feature set.

To change the order of the features, hover over the feature you want to move and click on the arrow.

Click an arrow to change the order of the features.
Figure 2. The Selected feature section in the Edit feature set pop-up. Click an arrow to change the feature order of the features.