Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Mtoto News Childline Kenya Call Volume Prediction Challenge

Domaine:

peace and security

Type de record:

dataset

Help Kenya's child protection hotline forecast how many calls they will receive each hour each day
The data have been split into a test and training set. The training set contains all the calls (over 135,000) that were received from 1 January 2016 to 12 July 2016. You are asked to estimate the number of incoming calls per hour per day from 13 July 2016 to 6 September 2016.
The files you have for download here are:
train.csv: Every call that was received from 1 January 2016 to 12 July 2016. You will use this file to train your model.
sample_submission.csv: Your submission CSV file should look like this. Note that the column"time_index" represents ONE HOUR time increments and the column "calls" represents the number of calls received during that one hour time period. The format of time_index is YYYYMMDDHH (year month day hour). For example, the calls associated with time_index 2016071300 would be the calls received between 12:00:00 am until 12:59:59 am on 13 July 2016.
KenyaPublicHolidays2016.csv: Public holidays in 2016
NairobiSchoolDates2016.csv: Academic term calendar for 2016
WeatherNairobi2016.xls: Weather data for Nairobi 2016. The source and explanation of variables can be found here.
Variables in Train.csv:
Each call contains the following fields
Variable Definition
calldate Date (month-day-year) and time of the call
cc_status Case status
maincat Main category call falls into
subcat1 Subcategory call falls under
casepriority Priority of the case
referal Place case referred to
caller_gender Gender of the caller
caller_age Age of the caller
caller_county Area where the call came from
child_age Age of the child in case
child_gender Gender of the child in case
child_county Area where the child is from
parent_age Age of the parent
parent_gender Gender of the parent
parent_county Area where the child is from
Abuser_Relationship Relationship abuser has with the child in case
Neglector_Relationship Relationship neglector has with the child in case
Physical_abuser_Relationship Relationship physical abuser has with the child in case

Visit

zindi.africa

Tags

competitionzindiforecasthealth

Similaires

Dehbaiyor/Mtoto-News-Childline-Kenya-Call-Volume-Prediction-ChallengeGabeOchieng/Winning_Solution_For_mtoto-news-childline-kenya-call-volume-prediction-challengeSharmaineMangombe/Childline-Kenya-Call-Volume-Prediction-Challenge

Dehbaiyor/Mtoto-News-Childline-Kenya-Call-Volume-Prediction-Challenge

This repo contains all the model iterations to help Kenya's child protection hotline forecast how ma

GabeOchieng/Winning_Solution_For_mtoto-news-childline-kenya-call-volume-prediction-challenge

This is a forcasting challenge at Zindi.Africa

SharmaineMangombe/Childline-Kenya-Call-Volume-Prediction-Challenge

# Childline Kenya Call Volume Prediction Challenge ## Overview This project is part of the Zindi co