README.md

metadata

dataset_info:
  - config_name: aligned
    features:
      - name: Tf
        sequence: float32
      - name: X
        sequence: float32
      - name: 'Y'
        sequence: float32
      - name: coefficients
        sequence: float32
      - name: f
        sequence: float32
    splits:
      - name: train
        num_bytes: 16360000
        num_examples: 10000
      - name: test
        num_bytes: 1636000
        num_examples: 1000
    download_size: 20519889
    dataset_size: 17996000
  - config_name: default
    features:
      - name: Tf
        sequence: float32
      - name: X
        sequence: float32
      - name: 'Y'
        sequence: float32
      - name: coefficients
        sequence: float32
      - name: f
        sequence: float32
    splits:
      - name: train
        num_bytes: 16360000
        num_examples: 10000
      - name: test
        num_bytes: 1636000
        num_examples: 1000
    download_size: 27175834
    dataset_size: 17996000
configs:
  - config_name: aligned
    data_files:
      - split: train
        path: aligned/train-*
      - split: test
        path: aligned/test-*
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*

Antiderivative Polynomial Dataset

Dataset Summary

The Antiderivative Polynomial dataset is a collection of polynomial functions and their antiderivatives. The dataset is generated using polynomial functions and their antiderivatives.

Plot from the dataset:

Dataset Structure

The dataset is structured as follows.

Subsets

The dataset is divided into two subsets:

• default: the default dataset.
• aligned: the X values are aligned for all functions.

Splits

The dataset is divided into two splits:

• train: the training split, consisting of 10,000 rows.
• test: the test split, consisting of 1,000 rows.

Columns

Each row in the dataset consists of the following columns:

• X: the input value of the function f.
• f: the value of the function f at X.
• Y: the input value of the antiderivative Tf.
• Tf: the value of the antiderivative Tf at Y.

Data

The dataset contains the following data:

Column	Shape	Type
X	(100,)	float
f	(100,)	float
Y	(100,)	float
Tf	(100,)	float