The 2st place solution for AutoSeries.

Download the competition's starting kit and run

python run_local_test.py --dataset_dir=./data/demo --code_dir=./code_submission

You can change the argument dataset_dir to other datasets, and change the argument dataset_dir to the directory (code_submission).

Each dataset containes 5 files: train.data, test.data, test.solution, test_time.data, info.yaml

This is the training data including target variable (regression target). Its column types could be read from info.yaml. There are 3 data types of features, indicated by "num", "str", and "timestamp", respectively: • num: numerical feature, a real value • str: string or categorical features • timestamp: time feature, an integer that indicates the UNIX timestamp

This is the test data including target variable (regression target). Its column types could be read from info.yaml.

This is the test solution (extracted from test.data).

This is the UNIQUE test timestamp (extracted from test.data).

For every dataset, we provide an info.yaml file that contains the important information (meta data).

Here we give details about info.yaml • time_budget : the time budgets for different methods in user models • schema : stores data type information of each column • is_multivariate: whether there are multiple time series. • is_relative_time: DEPRECATED, not used in this challenge. • primary_timestamp: UNIX timestamp • primary_id: a list of column names, identifying uniquely the time series. Note that if is_multivatriate is False, this will be an empty list. • label: regression target

Example:

DeepBlueAI: [email protected]