Ensemble learning prediction apparatus and method, and non-transitory computer-readable storage medium

An ensemble learning prediction apparatus, comprising:

• a loss module receiving a sample data and calculating a loss according to a first prediction result of the sample data and an actual result;
• a diversity module receiving the sample data and calculating a diversity between at least one hypothesis according to a second prediction result of the sample data under the at least one hypothesis;
• a sample weighting module calculating a correctable value of the sample data according to the first prediction result and the actual result and assigning a sample weight according to the correctable value;
• and
• an integrating weighting module, interconnected with the loss module, the diversity module and the sample weighting module, creating an object function according to the loss, the diversity and the sample weight, and training an ensemble weight by use of the object function;
• wherein an adaptive ensemble weight is calculated by integrating the ensemble weight and the ensemble weight obtained at previous time points, and the correctable value is obtained according to a function having a high point from which the function descends to both sides on which the high point no more appears.