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公开(公告)号：US20230267351A1
公开(公告)日：2023-08-24
申请号：US17939778
申请日：2022-09-07
Applicant: Hitachi, Ltd.
Inventor： Hiroyuki NAMBA , Masaki HAMAMOTO , Masashi EGI
CPC classification number: G06N5/045 , G06K9/6235 , G06K2009/6237
Abstract: A generation apparatus is configured to access a set of pieces of learning data each being a combination of a value of an explanatory variable and a value of an objective variable, a function family list including, of functions each indicating a physical law and an attribute of each of the functions, at least the functions, and search range limiting information for limiting a search range of the function family list, wherein the processor is configured to execute: first generation processing of generating a first prediction expression by setting a first parameter for the explanatory variable to a first function included in the function family list; first calculation processing of calculating, based on the search range limiting information, a first conviction degree relating to the first prediction expression; and first output processing of outputting the first prediction expression and the first conviction degree.
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公开(公告)号：US20220156602A1
公开(公告)日：2022-05-19
申请号：US17477314
申请日：2021-09-16
Applicant: Hitachi, Ltd.
Inventor： Hiroyuki NAMBA , Masashi EGI , Masaki HAMAMOTO , Masakazu TAKAHASHI
IPC: G06N5/02
Abstract: In classification problems or regression problems, a prediction rule that is highly accurate, simple, and in match with the knowledge of experts is obtained. A system includes a prediction rule simplification unit that simplifies a prediction rule of a learning model using an evaluation metric and a restriction; a branch condition search unit that updates a part of the simplified branch condition for prediction rule based on calibration information expressing a request for a prediction value or a specific branch condition; and a threshold optimization unit that updates a part of a threshold of the simplified prediction rule based on the calibration information.
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公开(公告)号：US20230410488A1
公开(公告)日：2023-12-21
申请号：US18036212
申请日：2021-11-22
Applicant: Hitachi, Ltd.
Inventor： Masaki HAMAMOTO , Masashi EGI , Masakazu TAKAHASHI , Hiroyuki NAMBA
IPC: G06V10/80 , G06V10/778
CPC classification number: G06V10/80 , G06V10/7788
Abstract: A predictor creation device including a processor configured to execute a program and a storage device that stores the program acquires a calibration target ensemble predictor obtained by combining a plurality of predictors based on a training data set which is a combination of training data and ground truth data, calculates a prediction basis characteristic related to a feature of the training data for each of the plurality of predictors, acquires an expected prediction basis characteristic related to the feature based on the prediction basis characteristic related to the feature as a result of outputting the prediction basis characteristic related to the calculated feature, determines a combination coefficient of each of the plurality of predictors based on the prediction basis characteristic related to the feature and the expected prediction basis characteristic related to the feature, and calibrates the calibration target ensemble predictor based on the combination coefficient.
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Patent Agency Ranking
公开(公告)号：US20210326724A1
公开(公告)日：2021-10-21
申请号：US17190834
申请日：2021-03-03
Applicant: HITACHI, LTD.
Inventor： Atsushi TOMODA , Hiroyuki NAMBA
Abstract: A hypothesis evaluation system evaluates a hypothesis for a work efficiently and appropriately, and is configured to store, for a work whose efficiency is desired to be improved, a hypothesis defined by using, as elements, one or more combinations of a feature amount representing the work and a condition imposed on the feature amount, and a target index of the efficiency, generate a plurality of measures in which a value of the feature amount is set around a threshold that determines a range of the feature amount so as to satisfy the condition, store an estimation value of the efficiency for each of the measures, the estimation value being acquired by executing the measure, compare the estimation value with the target index to determine whether or not the hypothesis is established for each of the measures, and set the threshold based on a result of the determination.
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5.发明申请公开(公告)号：US20200034738A1
公开(公告)日：2020-01-30
申请号：US16504897
申请日：2019-07-08
Applicant: Hitachi, Ltd.
Inventor： Masashi EGI , Yuxin LIANG , Naoaki YOKOI , Masayoshi MASE , Naofumi HAMA , Yasuhide MORI , Hiroyuki NAMBA
Abstract: There is provided is a computer system that outputs a predicted value of data to be evaluated using a predictor generated using learning data. The computer system includes the predictor; an index calculation unit that calculates an interpretation index of the data to be evaluated; and an extraction unit that selects the learning data useful for a user to interpret the predicted value of the data to be evaluated, wherein index management information for managing an interpretation index of the learning data is stored, the index calculation unit calculates the interpretation index of the data to be evaluated, and the extraction unit calculates a selection index based on the interpretation index of the data to be evaluated and the interpretation index of the learning data, selects the learning data based on the selection index, and outputs display information for presenting information indicating a processing result.
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公开(公告)号：US20190266619A1
公开(公告)日：2019-08-29
申请号：US16122924
申请日：2018-09-06
Applicant: Hitachi, Ltd.
Inventor： Hiroyuki NAMBA , Masaharu UKEDA
Abstract: A change in a behavior pattern contributing to improving a Key Performance Indicator (KPI) is discovered from among changes in the behavior pattern arising in common among customers having a specific characteristic. A behavior pattern search system classifies transfiguration candidates that are customers satisfying transfiguration result information. The transfiguration result information indicates a characteristic purchase behavior predicted to occur by a change in a behavior pattern of each of the customers.
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公开(公告)号：US20220270115A1
公开(公告)日：2022-08-25
申请号：US17439493
申请日：2020-12-16
Applicant: HITACHI, LTD.
Inventor： Kazuki YAMANE , Kazuaki TOKUNAGA , Kazuyuki OOTA , Hiroyuki NAMBA
Abstract: A learner generation unit generates, as a learner group, a plurality of learners that learned a correspondence of an attribute and an outcome in each of a plurality of learning data sets extracted from a data group associated with an attribute and an outcome of each of the targets. A target selection unit applies the learner group selected for inference to an inference data set and predicts, for each of the learners, an outcome corresponding to an attribute in the inference data set, calculates, for each attribute in the inference data set, at least one of an average of the outcomes predicted for each of the learners or an index value expressing an uncertainty of the outcomes, and selects, from the inference data set, the target to which the policy is to be executed based on at least one of the calculated average or the calculated index value.
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公开(公告)号：US20200234219A1
公开(公告)日：2020-07-23
申请号：US16554107
申请日：2019-08-28
Applicant: HITACHI, LTD.
Inventor： Hiroyuki NAMBA , Atsushi TOMODA , Hiromitsu NAKAGAWA , Masashi EGI
Abstract: A DB server 2 stores work achievement table 210 indicating a disposition target related to a work, an actual disposition place where the disposition target is disposed, and actual work time taken for the work for each work and location information 220 indicating a plurality of disposition places where the disposition targets can be disposed. A control portion 330 acquires a mutual action search policy including a plurality of mutual action emergence patterns indicating a relation between the two disposition places influencing the work time taken for the work. A generating portion (an item combination extraction portion 350, a mutual action set search portion 360, and a disposition change optimization portion 370) generates a disposition plan indicating a plan of disposition place where the disposition target is disposed on the basis of the work achievement information, the location information, and the mutual action search policy.
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