Method system and computer program product for visualizing an evidence classifier

• US 6,460,049 B1
• Filed: 12/22/1998
• Issued: 10/01/2002
• Est. Priority Date: 12/22/1998
• Status: Expired due to Term

• Current Assignee: RPX Corporation
• Original Assignee: Silicon Graphics Incorporated (Graphics Properties Holdings, Inc.)
• Inventors: Sommerfield, Daniel A., Tesler, Joel D., Becker, Barry G., Kohavi, Ron
• Primary Examiner(s): Coby, Frantz
• Application Number:
  US09/218,445
• Time in Patent Office: 1,379 Days
• Field of Search: 707/104, 707/100, 707/101, 707/102, 707/103
• US Class Current: 707/778
• CPC Class Codes: G06F 16/355 Class or cluster creation or modification
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

A method, system, and computer program product visualizes the structure of an evidence classifier. An evidence inducer generates an evidence classifier based on a training set of labeled records. A mapping module generates visualization data files. An evidence visualization tool uses the visualization data files to display an evidence pane and/or a label probability pane. A first evidence pane display view shows a normalized conditional probability of each label value, for each attribute value. The first evidence pane display view can be a plurality of rows of pie charts. Each pie slice in a pie chart has a size which is a function of the normalized conditional probability of each label value for the respective attribute value. For each pie chart, the mapping module maps a height that is a function of the number of records in the training set associated with the evidence classifier. A second evidence pane display view shows relative conditional probabilities of a selected label value, for each attribute value. The second evidence pane display view can be a plurality of rows of bars. Bar height is a function of a conditional probability of a respective attribute value conditioned on the selected label value. Bar heights can represent Evidence For a selected label value or Evidence Against a selected label. A first label probability pane display view shows a pie chart of prior probabilities of each label value based on the training set. A second label probability pane display view shows a pie chart of posterior probabilities of each label value based on at least one selected attribute value. An importance slider controls filtering of attributes based on the importance of the attributes to a classification of unlabeled records. A count slider filters out attribute values having relatively low record counts. The evidence classifier visualization tool further provides sorting of attributes and/or attribute values. A subtracting minimum evidence capability is provided.

Claims

1. An integrated data mining system comprising:

an evidence inducer;

means for configuring said evidence inducer to generate a first data file representing structure of an evidence classifier and a second data file representing structure of a decision-tree classifier;

means for visualizing said evidence classifier structure based on said first data file; and

means for visualizing said decision-tree classifier structure based on said second data file.