Abstract: An analysis apparatus according to one embodiment includes: an obtainment unit configured to obtain a data set of multiple data items having randomness; and an analysis unit configured to calculate, as an inner product or a norm of probability measures ? and ? being probability measures on the data set and taking values in a von Neumann algebra, by using a mapping ? that extends kernel mean embedding, an inner product or a norm of ?(?) and ?(?) mapped onto an RKHM.

Abstract: A relationship extraction device includes a memory; and a processor configured to execute obtaining a set of data {x0, . . . , xT?1}?X each having multiple elements and a set of data {y0=f(x0), . . . , yT?1=f(xT?1)}?Y each having multiple elements, where f is any mapping; generating an approximate operator that approximates a Perron-Frobenius operator K satisfying K?1(xt)=?2(yt) for t=0, . . . , T?1, wherein ?1 is a feature mapping with respect to a positive definite kernel function k1 on X×X that takes C*-algebra values, and ?2 is a feature mapping with respect to a positive definite kernel function k2 on Y×Y that takes C*-algebra values; obtaining data xt and xs as targets of relationship extraction; and extracting a relationship between each element of xt and each element of xs by using the approximate operator.

Abstract: A musicality information provision method includes acquiring first performance data from a performance of a given composition, calculating, with respect to a combination of a plurality of parameters indicating musicality, which are included in the first performance data, respective distances between the first performance data and a plurality of sets of second performance data that are acquired from performances of the given composition and that are compared with the first performance data, and outputting determination information for determining the musicality of the first performance data, the determination information including information indicating the distances.

Abstract: An anomaly detection apparatus includes an approximation unit configured to generate, based on observed data, an approximation of a Perron-Frobenius operator on an RKHS that represents a mathematical model to generate the observed data; and a detection unit configured to use the approximation of the Perron-Frobenius operator and an observed data item at time t, to predict a data item at time t+1, and based on a discrepancy between the predicted data item and an observed data item at time t+1, to determine whether the observed data item at time t+1 is anomalous.

Abstract: A musicality information provision method includes acquiring first performance data from a performance of a given composition, calculating, with respect to a combination of a plurality of parameters indicating musicality, which are included in the first performance data, respective distances between the first performance data and a plurality of sets of second performance data that are acquired from performances of the given composition and that are compared with the first performance data, and outputting determination information for determining the musicality of the first performance data, the determination information including information indicating the distances.

Abstract: In an evaluation information provision system, subject's motion data is stored in association with attributes. When an attribute is assigned, the evaluation information provision system selects feature data from a plurality of the subject's motion data associated with the assigned attribute. The evaluation information provision system calculates a score for the assigned attribute, for the user's motion, using a statistical distance between the selected feature data and the user's motion data. The calculated score is displayed, for example, as a screen.

Abstract: In an evaluation information provision system, subject's motion data is stored in association with attributes. When an attribute is assigned, the evaluation information provision system selects feature data from a plurality of the subject's motion data associated with the assigned attribute. The evaluation information provision system calculates a score for the assigned attribute, for the user's motion, using a statistical distance between the selected feature data and the user's motion data. The calculated score is displayed, for example, as a screen.

Abstract: A multidimensional data visualization apparatus capable of visualizing a data distribution in an input space of high-dimensional data so as to enable understanding of relationships between input dimensions is provided. Low-dimensional parallel coordinates plot creation element 71 creates, from input multidimensional data, a plurality of low-dimensional parallel coordinates plots that are each a graph in which data relating to part of dimensions in the multidimensional data is represented by a parallel coordinates plot. Feature value computation element 72 computes, for each pair of low-dimensional parallel coordinates plots, a feature value indicating a relationship between the low-dimensional parallel coordinates plots forming the pair. Coordinate computation element 73 computes coordinates at which each low-dimensional parallel coordinates plot is arranged, based on the feature value computed by the feature value computation element 72.

Abstract: To provide a discriminant model learning device capable of efficiently learning a discriminant model on which domain knowledge indicating user's knowledge or analysis intention for a model is reflected while keeping fitting to data. A query candidate storage means 81 stores candidates of a query as a model to be given with domain knowledge indicating a user's intention. A regularization function generation means 82 generates a regularization function indicating compatibility with domain knowledge based on the domain knowledge to be given to the query candidates. A model learning means 83 learns a discriminant model by optimizing a function defined by a loss function and the regularization function predefined per discriminant model.

Abstract: An optimality degree computation unit computes an optimality degree in the case where a first variable included in a variable set is a candidate for an addition variable, using an objective function. An addition threshold computation unit computes an addition threshold based on the computed optimality degree, the addition threshold being a threshold of the optimality degree and indicating a criterion for determining whether or not the first variable is to be set as the candidate for the addition variable. An objective function value computation unit computes an objective function value which is a difference between a value of the objective function computed using variables to be optimized and a value of the objective function computed using the variables to be optimized from which a second variable included in a nonzero variable set is excluded.

Abstract: To provide a discriminant model learning device capable of efficiently learning a discriminant model on which domain knowledge indicating user's knowledge or analysis intention for a model is reflected while keeping fitting to data. A query candidate storage means 81 stores candidates of a query as a model to be given with domain knowledge indicating a user's intention. A regularization function generation means 82 generates a regularization function indicating compatibility with domain knowledge based on the domain knowledge to be given to the query candidates. A model learning means 83 learns a discriminant model by optimizing a function defined by a loss function and the regularization function predefined per discriminant model.

Abstract: To provide an optimized query generating device capable of generating an optimized query to be given with domain knowledge when generating a discriminant model on which the domain knowledge indicating user's knowledge or analysis intention for a model is reflected. A query candidate storage means 86 stores candidates of a query which is a model to be given with domain knowledge indicating a user's intention. An optimized query extraction means 87 extracts queries having low uncertainty of a discriminant model estimated by queries given with domain knowledge when the domain knowledge is given thereto from query candidates.

Abstract: A knock-down type mailing parcel case which comprises a rectangular cardboard main body having the opposite inwardly folded side edges and a pair of rectangular cardboard flaps extending perpendicular to the longitudinal axis of the main body and secured at one end to the folded side edges. The flaps have the length substantially greater than one half of the width of the main body, but smaller than the full width of the main body so that the flaps overlap one upon another covering a substantial area of the flaps. The flaps have folding lines extending transversely of the flaps and positioned adjacent to the secured ends and the main body has two groups of folding lines extending transversely of the main body and positioned adjacent to and outside the folding lines on the flaps.