# DABench Task 549 - Explore the correlation between the length and the weight of the whole abalone. Additionally, perform feature engineering by creating a new feature called "volume" by multiplying the length, diameter, and height of the abalone. Determine if the volume feature improves the accuracy of predicting the number of rings using a linear regression model.

## Task Description

Explore the correlation between the length and the weight of the whole abalone. Additionally, perform feature engineering by creating a new feature called "volume" by multiplying the length, diameter, and height of the abalone. Determine if the volume feature improves the accuracy of predicting the number of rings using a linear regression model.

## Concepts

Correlation Analysis, Feature Engineering, Machine Learning

## Data Description

Dataset file: `abalone.csv`

The data is available in the `train.csv` file in the public directory.

## Constraints

Calculate the Pearson correlation coefficient to assess the strength and direction of the linear relationship between length and the weight. The volume feature should be created by multiplying the length, diameter, and height of the abalone. Use the sklearn's linear regression model to predict the number of rings. Split the data into a 70% train set and a 30% test set. Evaluate the models by calculating the root mean squared error (RMSE) with the test set.

## Files

- `train.csv` - The training data
- `sample_submission.csv` - A sample submission file in the correct format

## Submission Format

Submit a single-row CSV with columns `id,answer`.

- `id`: always `549`
- `answer`: three key-value pairs separated by spaces: `@volume_feature_model_rmse[<number>] @correlation_coefficient[<number>] @original_model_rmse[<number>]`

Each `<number>` is rounded to four decimal places.

## Evaluation

Submissions are evaluated on **exact match** with the ground truth answer (with tolerance of 0.01 for floating-point values).

## Goal

Provide the correct answer in the specified format.

## Difficulty Level

Hard
