Abstract: An information processing apparatus includes a data acquisition unit that acquires data including a missing value, a missing rate calculation unit that calculates a missing rate indicating a ratio of missing values included in the data, and a covariance matrix estimation unit that estimates a covariance matrix based on the missing rate. According to the information processing apparatus, since the covariance matrix is estimated based on the missing rate, the estimation accuracy of the covariance matrix can be improved.

Abstract: An information processing apparatus includes a data acquisition unit that acquires data including a missing value, a missing rate calculation unit that calculates a missing rate indicating a ratio of missing values included in the data, and a covariance matrix estimation unit that estimates a covariance matrix based on the missing rate. According to the information processing apparatus, since the covariance matrix is estimated based on the missing rate, the estimation accuracy of the covariance matrix can be improved.

Abstract: In a clustering apparatus comprising an input unit (1) supplied with a dataset including a plurality of samples, a data processing unit (4) for processing the samples to classify each sample into a class, and an output unit (3) for producing a processing result representative of classification, a parameter memory (51) in a memory unit (5) memorizes a target parameter obtained from past experiment. A parameter estimating section (24) of the data processing unit estimates a clustering parameter by the use of the target parameter memorized in the parameter memory. An unidentifiable sample detecting section (25) of the data processing unit detects a sample as an unidentifiable sample if posterior probabilities calculated for the sample by a probability density function produced by the clustering parameter estimated by the parameter estimating section are smaller than a predetermined value.