## Overview

The data has been split into two groups:
- training set (**train.csv**)
- test set (**test.csv**)

The training set should be used to build your machine learning models. For the training set, we provide the label (also known as the “ground truth”) for each gene. Your model will be based on the sequence. You can use feature engineering to create new features.

The test set should be used to see how well your model performs on unseen data. For the test set, we do not provide the ground truth for each gene. It is your job to predict these labels. For each sequence in the test set, use the model you trained to predict whether or not it is a plant resistance gene. This set will be used for evaluation and team ranking.

We also include **sample_submission.csv**, a set of random predictions, as an example of what a submission file should look like.

## Columns

* `ID` - unique protein identifier
* `Sequence` - protein sequence
* `Label` - protein class; 1 for plant resistance gene, 0 otherwise