Recently, there has been an increase in the number of building collapse in Lagos and major cities in Nigeria. Olusola Insurance Company offers a building insurance policy that protects buildings against damages that could be caused by a FIRE or VANDALISM, by a FLOOD or STORM.
Insurance-Predition
Zindi Project from DSN ML Open Competition
Data Science Nigeria 2019 Challenge #1: Insurance Prediction
Description of the challenge:
Recently, there has been an increase in the number of building collapse in Lagos and major cities
in Nigeria. Olusola Insurance Company offers a building insurance policy that protects buildings
against damages that could be caused by a FIRE or VANDALISM, by a FLOOD or STORM.
You have been appointed as the Lead Data Analyst to BUILD a PREDICTIVE MODEL to determine
if a building will have an INSURANCE CLAIM during a certain period or NOT. You will have to
PREDICT THE PROBABILITY of having AT LEAST ONE CLAIM OVER THE INSURED PERIOD of the building.
Most categorical data like Building_Painted, Building_Fenced, Garden, Settlement are
converted using map encoding to 0 and 1.
THE MODEL WILL BE BASED ON THE BUILDING CHARACTERISTICS, which includes:
NumberOfWindows, Building.Dimension, Building_Painted, Building_Fenced, Garden.
The target variable, Claim, is a:
1 if the building has at least a claim over the insured period.
0 if the building doesn't have a claim over the insured period.
Predictor Variables: Insured_Period, NumberOfWindows, Building.Dimension, Building_Painted,
Building_Fenced, Garden.
Target Variable: Claim (At least one claim:1, No claim:0)
Logistic Regression(LR) Algorithm (A Type of Classification algorithm under the Supervised
Learning type of ML)
LR returns binary result unlike in statistics where regression implies continuous values. The
algorithm measures the relationship between features are weighted and impact the result
(1 and 0; in this case, 1, if the building has at least one claim over the insured period
or 0, if the building doesn't have a claim over the insured period, no claim)