{% extends "global/Page.html" %}
{% load otree static %}

{% block title %}
    Information about the ML algorithm
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{% block content %}


    <p>
        For creating a forecast, the ML algorithm takes the following <strong>15 features</strong> into account:
        <ul>
            <li><strong>Average values of historical data</strong> (6 features)</li>
                <ul>
                    <li><strong>Avg_total</strong>: Average of all previous data points</li>
                    <li><strong>Avg_year</strong>: Average of all previous data points which have the same year value as the upcoming forecast to
                    be made (e.g. all data points of 2017)</li>
                    <li><strong>Avg_quarter</strong>: Average of all previous data points which have the same quarter value as the upcoming forecast to
                    be made (e.g. all data points in first quarter, no matter which year) </li>
                    <li><strong>Avg_month</strong>: Average of all previous data points which have the same month value as the upcoming forecast to
                    be made (e.g. all historical data points in January, no matter which year)</li>
                    <li><strong>Avg_week</strong>: Average of all previous data points which have the same week value as the upcoming forecast to
                    be made (e.g. all data points of calender week 42, no matter which year)</li>
                    <li><strong>Avg_weekday</strong>: Average of all previous data points which have the same weekday value as the upcoming forecast to
                    be made (e.g. all data points on a Monday, no matter which week, month, quarter or year)</li>
                </ul>
            <li><strong>Past actual values</strong> (9 features)</li>
                <ul>
                    <li><strong>{1-6}_day(s)_ago</strong>: Actual demand value 1, 2, 3, 4, 5 or 6 day(s) ago (6 features) </li>
                    <li><strong>1_week_ago</strong>: Actual demand value 1 week ago </li>
                    <li><strong>1_month_ago</strong>: Actual demand value 1 month ago (4*7 days ago) </li>
                    <li><strong>1_year_ago</strong>: Actual demand value 1 year ago (52*7 days ago) </li>
                </ul>
        </ul>
    </p>

{% comment %}
    <h4>How good?</h4>
    <p>
        The algorithm was put together by thoughtful analysts and has an average accuracy of ~92%.
        (TBD) "a sophisticated model, put together by thoughtful analysts"
    </p>
{% endcomment %}

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