Random Forest Regression models for Lactation and Successful Insemination in Holstein Friesian cows. 1. Mathematical aspects

The random forest regression (RFR) method is applied to study dairy cows’ economical breeding and milk production over- come well-known difficulties in establishing reliable models based on large data sets. Regarding the features of RFR, there are sev- eral positive experiences various areas applications supporting that with one can achieve model predictions for industrial any product providing a useful base decisions. In this study, set compiled over decade about 80,000 cows, was analyzed through RFR. Ranking control parameters obtained, most important explanatory variables found by computing variances target variable sets created during training phases Predictions made calves’ conception high accuracy given data, simulations used investigate prediction accuracy. This primarily concerned mathematical aspects forthcoming article focuses agricultural aspects. results will be compared factor analysis linear future research plans.