Visualization device, visualization method and visualization program

A visualization device, comprising:

• a memory;
• and
• a processor coupled to the memory and programmed to perform operations comprising:
• presenting centrality values of a plurality of features, wherein:
• the centrality values of the plurality of features are calculated based on a centrality analysis of an adjacency matrix of pairs of features;
• the pairs of features are identified from the plurality of features;
• the adjacency matrix is generated using weights respectively corresponding to the pairs of features;
• and
• the weights are calculated based on at least one of a correlation analysis, an importance analysis, a prediction rule analysis, or a responsiveness analysis, wherein the respective weights indicate a strength of a relationship between the corresponding pair of features;
• obtaining a feature selected by a user based on the presented centrality values of the plurality of features;
• and
• drawing a relationship between features including the combination of features including the selected feature, based on the combination of features including the selected feature and a predetermined visualization system corresponding to the combination of features including the selected feature.

A visualization method executed by a visualization device, comprising:

• obtaining input data;
• extracting a plurality of features from the input data;
• identifying pairs of features from the plurality of features;
• calculating weights respectively corresponding to the pairs of features based on at least one of a correlation analysis, an importance analysis, a prediction rule analysis, or a responsiveness analysis, wherein the respective weight indicates a strength of a relationship between the corresponding pair of features;
• generating, using the calculated weights, an adjacency matrix of the pairs of features;
• calculating centrality values of the plurality of features based on a centrality analysis of the adjacency matrix of the pairs of features;
• extracting a combination of features from the plurality of features based on the centrality values of the plurality of features;
• identifying a visualization system for the extracted combination of features in accordance with at least types and connection relationships of features included in the extracted combination of features;
• and
• drawing a relationship between the features included in the extracted combination of features in order of priority according to the calculated centrality values, based on the extracted combination of features and the visualization system corresponding to the extracted combination of features.

A non-transitory computer-readable recording medium having stored a visualization program that, when executed by a processor, causes the processor to perform operations, comprising:

• obtaining input data;
• extracting a plurality of features from the input data;
• identifying pairs of features from the plurality of features;
• calculating weights respectively corresponding to the pairs of features based on at least one of a correlation analysis, an importance analysis, a prediction rule analysis, or a responsiveness analysis, wherein the respective weight indicates a strength of a relationship between the corresponding pair of features;
• generating, using the calculated weights, an adjacency matrix of the pairs of features;
• calculating centrality values of the plurality of feature based on a centrality analysis of the adjacency matrix of the pairs of features;
• extracting a combination of features from the plurality of features based on the centrality values of the plurality of features;
• identifying a visualization system for the extracted combination of features in accordance with at least types and connection relationships of features included in the extracted combination of features;
• and
• a drawing step of drawing a relationship between the features included in the extracted combination of features in order of priority according to the calculated centrality values, based on the extracted combination of features and the visualization system corresponding to the extracted combination of features.