# Calorie Consumption

*English translation by SOTA – AI Community of the Romanian original, published with the permission of Asociația Nitro. Organisers who would like this translation removed can email team@sota-ai.org.*

## Statement
Implement an AI/ML model to predict the calorie consumption of an activity, given a training set `train_data.csv` and the test set `test_data.csv` (on which you only need to make predictions).

The dataset contains the following fields, with these meanings:

- `User_ID`: the ID of the user who performed the activity
- `Gender`: the user's gender
- `Age`: the user's age
- `Height`: the user's height in cm
- `Weight`: the user's weight in kg
- `Duration`: the duration of the activity
- `Heart_Rate`: the average heart rate during the activity
- `Body_Temp`: the average temperature during the activity
- `Calories`: the number of calories consumed during the activity (present only in the training dataset)

## Notes on the dataset:

The target attribute is `Calories`. Given the other attributes, the goal is to predict `Calories` for the test dataset. The evaluation metric used is MAE (the mean of the absolute differences between the value predicted by the algorithm and the correct value).

## Requirements

**Part 1 (20p)**. Based on the training dataset, compute the following:

"Samples, No.Males, AverageDuration, SeniorUsers"

- **Subtask 1**: `Samples`: the number of rows in the training dataset
- **Subtask 2**: `No.Males`: the number of training examples that describe activities performed by men
- **Subtask 3**: `AverageDuration`: the average duration of the activities in the training set.
- **Subtask 4**: `SeniorUsers`: the number of users in the training set who are at least 75 years old

Each of the 4 subtasks is worth 5p.

**Part 2 (80p)**

- **Subtask 5: (60p)** Develop an AI/ML model and predict the `Calories` attribute for each example in the test data file for which the `Subtask` column has the value 5.

- **Subtask 6: (20p)** A men's handball team needs to estimate calorie consumption in order to optimise the players' diet. Develop an AI/ML model and predict the number of calories for each example in the test data file for which the `Subtask` column has the value 6.

## Output format

A csv file `output.csv` that includes the following 3 columns:
- `subtaskID` - the number of the subtask (1, 2, 3, 4, 5 or 6)
- `datapointID` - which refers to the `User_ID` column in `test_data.csv`
- `answer` - the answer corresponding to the datapoint for the respective subtask

**Note:** For subtasks 1, 2, 3 and 4, which require a single answer for the whole dataset, output a single row whose `datapointID` is 1.

Submit a single csv containing the answers for all the subtasks you have solved. To see an example, download the file `sample_output.csv`