The conflict between validity and extensibility can be solved by using a multi-side increase by degrees algorithm(shortened form MIDA) at machine learning in a data set with a feature space of high dimensionality and with large amount of samples that belong to many different classes.In the algorithm

the sample set is divided into several sample subsets step by step by double-point.These feature subsets to match each sample set may be extracted at the same time.The method of different treatment to each sample subset is similas to that facing difficult problems people consider and seek a answer from different emphases and multi sides.The algorithm can classify the difficult problems effectually and raise the extensibility and reduce the complexity in condition of established accuracy.The multi-side increase by degrees algorithm bases on a covering algorithm at machine learning.MIDA is used to classify a date set from Shanghai's stock

and the result is satisfied.