House_Price_prediction_XGB_Regressor

Predictive Model built on XGB Boost Regressor to predict the house price using a set of features that describe a house in Boston.

ZN:

proportion of residential land zoned for lots over 25,000 sq.ft.

INDUS:

proportion of non-retail business acres per town

CHAS:

Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)

NOX:

nitric oxides concentration (parts per 10 million) 1https://archive.ics.uci.edu/ml/datasets/Housing 123 20.2. Load the Dataset 124

RM:

average number of rooms per dwelling

AGE:

proportion of owner-occupied units built prior to 1940

DIS:

weighted distances to five Boston employment centers

RAD:

index of accessibility to radial highways

TAX:

full-value property-tax rate per $10,000

PTRATIO:

pupil-teacher ratio by town 12. B: 1000(Bk−0.63)2 where Bk is the proportion of blacks by town 13. LSTAT: % lower status of the population

MEDV:

Median value of owner-occupied homes in $1000s We can see that the input attributes have a mixture of units.