The invention relates to a pet health discrimination method and device based on a gradient lifting xgboost model. The method comprises the following steps: S1, acquiring a historical detection data
record of an intelligent pet cat
litter basin; s2, performing
data set division and xgboost model
verification and training on the historical detection data by adopting a
data set division method of ten-fold
cross validation, and optimizing the xgboost model in each
cross validation; s3, performing identification model training based on an xgboost
algorithm according to the historical detection data to obtain a cat
health condition discrimination model corresponding to the intelligent pet cat
litter basin and
health index importance corresponding to the pet cat
litter basin; s4, monitoring the performance of the xgboost model, and performing incremental updating of the pet health discrimination model and
continuous optimization of
feature selection according to historical detection data and new detection data; and S5,
smoothing the pet
health index to obtain a warning threshold value of the intelligent pet cat
litter box, and when the real-time detection data of the intelligent pet cat
litter box exceeds the warning threshold value, performing pet health abnormity warning on a pet owner.