A proposal for a new method of classification of objects of various nature, named "2"-soft classification, which allows to refer objects to one of two types with optimal entropy probability for available collection of learning data with consideration of additive errors therein. A decision rule of randomized parameters and probability density function (PDF) is formed, which is determined by the solution of the problem of the functional entropy linear programming. A procedure for "2"-soft classification is developed, consisting of the computer simulation of the randomized decision rule with optimal entropy PDF parameters. Examples are provided.