Climate feature factor extraction method based on combination of supervised learning and unsupervised learning

The invention provides a climate feature factor extraction method based on combination of supervised learning and unsupervised learning. The method comprises the steps of obtaining historical data of factors; wherein the historical data of the factors comprises historical data of physical quantity field factors and historical data of forecast objects; standardizing the historical data of the factors to obtain standardized data; analyzing the standardized data by adopting a supervised learning regression class, and extracting a mean square error field of the standardized data; analyzing the standardized data by adopting a correlation coefficient class, and extracting a correlation coefficient field of the standardized data; acquiring a forecast factor set of a mean square error field; acquiring a forecast factor set of the correlation coefficient field; and merging the forecast factor set of the mean square error field and the forecast factor set of the correlation coefficient field to obtain a multi-factor se