Class AmesRandomAccess

  • All Implemented Interfaces:
    ai.djl.training.dataset.Dataset

    public class AmesRandomAccess
    extends CsvDataset
    Ames house pricing dataset from https://www.kaggle.com/c/house-prices-advanced-regression-techniques/data.

    80 features

    Training Set: 1460 Records

    Test Set: 1459 Records

    Can enable/disable features Set one hot vector for categorical variables

    Call AmesRandomAccess.Builder.addAllFeatures() to include all features from the dataset. The label is a numeric column named "saleprice".

    • Method Detail

      • prepare

        public void prepare​(ai.djl.util.Progress progress)
                     throws java.io.IOException
        Specified by:
        prepare in interface ai.djl.training.dataset.Dataset
        Overrides:
        prepare in class CsvDataset
        Throws:
        java.io.IOException