9. The machine learning system according to claim 7 , wherein said second feature set comprises one or more of: a maximum value of said first confidence degrees; a difference between said maximum value and a second maximum value of said first confidence degrees; an average of said first confidence degrees; an average of an important feature in said first feature set; and a standard deviation of an important feature in said first feature set.
7. A machine learning system for computer question-answering, comprising: means configured to receive a plurality of questions to be trained, and obtain a candidate answer set for each question; means configured to determine a part of said questions to which said candidate answer sets include correct answers, and use first feature sets of said candidate answers to which said part of said questions correspond to form a first input training data set, wherein said first feature sets comprises at least one of: a matching degree of a type of said candidate answer and said question to be trained; a literal similarity between the text around said candidate answer and the text of said question to be trained; a matching degree of a time feature of said candidate answer and the time appearing in said question to be trained; and a matching degree of a geographic location of said candidate answer and a geographic location appearing in said question to be trained; means configured to perform machine learning on said first input training data set to obtain a first mathematical model, and use said first mathematical model to compute a first confidence degree that said candidate answer is a correct answer based on said first feature set; means configured to compute first confidence degrees of said candidate answers of all of said questions to be trained, and for each question, extracting a second feature set related to said first confidence degrees and said first feature set; and means configured to perform machine learning on a second input training data set formed by said second feature sets of said plurality of questions to be trained, to obtain a second mathematic model, which is used to compute a second confidence degree that said candidate answer is a correct answer based on said second feature set.