Abstract: In predictive data mining, a process and tool presents a method to compare given competing algorithms to a derived reference, such as a baseline or benchmark. A result confidence as to the suitability of the competing algorithm to a given task is generated. In an exemplary embodiment, a randomized feature acting, simple, algorithm is used to generate the baseline. In an alternative embodiment, the process and tool is used to determine learnability of the given task. A mechanism to account for overfitting of data is described.

Abstract: A method of reporting the presentation of data, a data storage medium, and a system for employing a web page is disclosed and that includes accessing a source of data having a specific segment, and reporting a presentation of the specific segment to a remote location.

Abstract: A feature selection method for selecting a predetermined number of features, the method may comprise for each category, ranking features according to feature ranking for two-category problems; and while the predetermined number of features has not yet been selected: picking a category c; selecting a feature based on the ranking for category c; and adding the selecting feature to an output list if not already present in the output list and removing the selected feature from further consideration for the category c. An apparatus and computer program code are also provided.

Abstract: A method of evaluating multiple predetermined techniques, given a set of problems that the techniques are designed to be used on, the method comprising using each of the predetermined techniques on each of the problems and scoring the performance of each technique on each problem; recording, for each problem, the best obtainable score; and for a predetermined tolerance value, determining for each technique what percentage of the problems the technique scored within the tolerance value from the best obtainable score, and determining which technique has the highest percentage. An apparatus and computer program code are also provided.

Abstract: The present invention relates generally to the classification of items into categories, and more generally, to the automatic selection of different classifiers at different places within a hierarchy of categories. An exemplary hierarchical categorization method uses a hybrid of different classification technologies, with training-data based machine-learning classifiers preferably being used in those portions of the hierarchy above a dynamically defined boundary in which adequate training data is available, and with a-priori classification rules not requiring any such training-data being used below that boundary, thereby providing a novel hybrid categorization technology that is capable of leveraging the strengths of its components.

Abstract: A two-class analysis system for summarizing features and determining features appropriate to use in training a classifier related to a data mining operation. Exemplary embodiments describe how to select features which will be suited to training a classifier used for a two-class text classification problem. Bi-Normal Separation methods are defined wherein there is a measure of inverse cumulative distribution function of a standard probability distribution and representative of a difference between occurrences of the feature between said each class. In addition to training a classifier, the system provides a means of summarizing differences between classes.

Abstract: A method of efficiently migrating data from one categorization hierarchy to a new hierarchy. A mapping is created which describes where a document in one hierarchy will be placed in a new hierarchy. The classifier of the first hierarchy is merged with this mapping to act as a classifier for the second hierarchy. Cases from the first hierarchy are classified in the new hierarchy using this merged mapping. In another embodiment, a training set is designated from a first hierarchy and mapped to a second hierarchy. Using machine learning, a classifier for the second hierarchy is derived and used to classify subsequently migrated cases. Migration of data using the present invention is more accurate as fewer human errors are generated. The present invention can act as a virtual classifier for multiple hierarchies in an organization, providing updated categorization information for multiple hierarchical databases.

Abstract: An operating system feature for a computing device provides the ability to perform pre-launch subroutines of application programs on the device. A pool of pre-launched application programs is maintained such that a subsequent request for a program launch is married to the already pre-start instances. Provision is also made for monitoring available computing resources, dependencies, and user preferences to optimize device use with respect to launching application programs.

Abstract: A visualization method and tool for gaining insight into the structure of a hierarchy. A derived intuitive display of the relation and effect on classification of features in nodes in a classification hierarchy provides a snapshot of a metric, such as coherence of the hierarchy. The visualization tool displays, in a single view, all or part of the following information: which features are the most powerful in identifying a particular topic; how these features are distributed over items in its sub-classes; which of these features do strongly distinguish among, and help classify items into, subclasses, and which do not (the ones that are shared evenly among the sub-classes justify the grouping as being coherent); and topic relationships among subclasses.

Abstract: In prediction and machine-learning technology, using given information from a user and a set of choices (e.g., a hierarchy structure) and, using a classifier program, computing what is the next best choice for navigating the set of choices, or, more generally, the degree to which any choice at a current level is supported by the available information, i.e., a probability of success associated with each currently available choice. An interactive interface is provided between the user and the set owner that dynamically feeds back the results of classification to the user preferably at each navigation step, i.e., specifying probabilities, suggesting choices, or highlighting the best choice(s) or the path(s) most likely leading to the best ultimate choice of the set.

Abstract: A method for predicting parts for onsite repair which takes into account a repair history and the costs associated with mis-predictions. Parts for onsite repair of a product are predicted by determining an expected waste for one or more parts of the product. The parts having a lowest expected waste are selected and sent to the onsite repair. The expected waste indicates parts that are responsible for high support costs and highlights the mistakes being made and scores the mistakes by actual cost.

Abstract: A method of efficiently migrating data from one categorization hierarchy to a new hierarchy. A mapping is created which describes where a document in one hierarchy will be placed in a new hierarchy. The classifier of the first hierarchy is merged with this mapping to act as a classifier for the second hierarchy. Cases from the first hierarchy are classified in the new hierarchy using this merged mapping. In another embodiment, a training set is designated from a first hierarchy and mapped to a second hierarchy. Using machine learning, a classifier for the second hierarchy is derived and used to classify subsequently migrated cases. Migration of data using the present invention is more accurate as fewer human errors are generated. The present invention can act as a virtual classifier for multiple hierarchies in an organization, providing updated categorization information for multiple hierarchical databases.