Image for post
Image for post

MOTIVATION

In Sep 9th, 2020 I wrote a post where I discussed if a machine learning model could predict if farmers reach a living income, and why this is important.

Results where promising! The model was correct 96.5% of the time (accuracy). However, since only 15% of the farmers in the dataset reached a living income, a model can be highly accurate just by guessing no one will reach it. …


Image for post
Image for post

1. INTRODUCTION

In Sep 9th, 2020 I wrote a first post where I discussed if a machine learning model could predict if farmers (in Ghana and Côte d’Ivoire) reach a living income, and why this is important. In Dec 16th, 2020, I wrote a follow-up post where I presented a machine learning model tackling the same problem using only 9 variables and web app using the model.

This post is the technical companion. Here I go into the technical details behind the two posts above and explain my path from beginning to end.

2. PROJECT DEFINITION

2.1 Project Overview

As introduced in the first post, the Living Income…


Image for post
Image for post

INTRODUCTION

The Living Income Community of Practice has been making a tremendous job in developing a more challenging standard of living reference value: a minimum amount needed for a household to have a basic, but decent, standard of living.

This is higher than the poverty line and therefore harder to achieve. However, we all must agree that smallholder farmers (who produce a large amount of the food we consume) should not be living in (extreme) poverty.

Marcelo Tyszler

Translating complex problems into feasible solutions www.marcelotyszler.com

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store