International Business Machines Corporation

Barry Kumin Rosen

Vijay Sourirajan Iyengar

Gabriel M Silberman

Se June Hong

Brian F White

Fateh Ali Tipu

Edna Grossman

Zeev Barzilai

Edwin Peter Pednault

Hsueh-ju Wang

Chidanand Vinayak Apte

Zeev Barazilai

A method of boosting of predictive models, called cascade boosting, for resolving the interpretability problem of previous boosting methods while mitigating the fragmentation problem when applied to decision trees. This method of cascade boosting always applies a single weak model to any given data point. An improvement to the common method of boosting lies in how weak models are organized in a decision list rather than a weighted average. Cascade boosting resolves the interpretability problem of previous boosting methods while mitigating the fragmentation problem when applied to decision trees. Cascade boosting is simplest when applied to segmented predictive models but may also be applied to predictive models that do not explicitly segment the space of possible data points. The predictive model resulting from cascade boosting has fewer rules, or tree leaves, thereby enabling a modeler to better understand the correlations among the data.

Cascade boosting of predictive models

A computer implemented method of underwriting profitability analysis delivers the analytic process to a wide cross section of insurance decision makers. The underwriting profitability analysis system leverages an existing investment in databases and improves underwriting business processes. Data mining techniques are applied to historical policy and claims to extract rules that describe policy holders with homogeneous claim frequency and severity characteristics. These rule sets are used to classify policy holders into distinct risk groups, each with its own set of characteristics, including pure premium. Breaking up a book of business into segments allows identification of sub-populations of policy holders that distinctly deviate from the expected normal pure premium. This identification allow the insurance business analysts to interactively adjust eligibility criteria and examine altered characteristics of the covered segments until satisfactory. The system is implemented on a client server using network centric language technology.

Data mining based underwriting profitability analysis

A method for modeling complementary metal oxide semiconductor (CMOS) combinatorial logic circuits by Boolean gates taking into account circuit behavior effects due to charge storing and static hazards. Models are developed for both the faultless and faulty operation of each circuit. According to a further aspect of the invention, these models are used in a simulation procedure to evaluate the fault coverage of a large scale integrated circuit design built using a plurality of these circuits. In the evaluation procedure the faulty model is used only for a particular circuit whose failure performance is being tested and the faultless model is utilized for all other circuits. This procedure is continued until all of the individual gate circuits have been evaluated.

Method for the modeling and fault simulation of complementary metal

A method of simulating a differential cascode voltage switch circuit (domino circuit) by replacing each switch-level logic tree by a three-section Boolean tree. In each section, a switch is replaced by an AND gate. The first and third section pass signals in one direction and the second section passes signals in the opposite directions. The three sections are interconnected end to end. Various faults can be simulated by holding selected internal signals at faulty values.

Fault simulation for differential cascode voltage switches

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Stormville, NY, United States of America

Barry Kumin Rosen