SPACE EFFICIENT RANDOM DECISION FOREST MODELS IMPLEMENTATION UTILIZING AUTOMATA PROCESSORS

    公开(公告)号:US20200327453A1

    公开(公告)日:2020-10-15

    申请号:US16913582

    申请日:2020-06-26

    Abstract: An apparatus includes a processing resource configured to receive a feature vector of a data stream. The feature vector includes a set of feature values. The processing resource is further configured to calculate a set of feature labels based at least in part on the set of feature values to generate a label vector, provide the label vector to another processing resource, and to receive a plurality of classifications corresponding to each feature label of the label vector from the other processing resource. The plurality of classifications are generated based at least in part on a respective range of feature values of the set of feature values. The processing resource is configured to then combine the plurality of classifications to generate a final classification of the data stream.

    SPACE EFFICIENT RANDOM DECISION FOREST MODELS IMPLEMENTATION UTILIZING AUTOMATA PROCESSORS

    公开(公告)号:US20240185139A1

    公开(公告)日:2024-06-06

    申请号:US18439024

    申请日:2024-02-12

    CPC classification number: G06N20/20 G06N5/01 G06N20/00

    Abstract: An apparatus includes a processing resource configured to receive a feature vector of a data stream. The feature vector includes a set of feature values. The processing resource is further configured to calculate a set of feature labels based at least in part on the set of feature values to generate a label vector, provide the label vector to another processing resource, and to receive a plurality of classifications corresponding to each feature label of the label vector from the other processing resource. The plurality of classifications are generated based at least in part on a respective range of feature values of the set of feature values. The processing resource is configured to then combine the plurality of classifications to generate a final classification of the data stream.

    Space efficient random decision forest models implementation utilizing automata processors

    公开(公告)号:US10699213B2

    公开(公告)日:2020-06-30

    申请号:US15214188

    申请日:2016-07-19

    Abstract: An apparatus includes a processing resource configured to receive a feature vector of a data stream. The feature vector includes a set of feature values. The processing resource is further configured to calculate a set of feature labels based at least in part on the set of feature values to generate a label vector, provide the label vector to another processing resource, and to receive a plurality of classifications corresponding to each feature label of the label vector from the other processing resource. The plurality of classifications are generated based at least in part on a respective range of feature values of the set of feature values. The processing resource is configured to then combine the plurality of classifications to generate a final classification of the data stream.

    Space efficient random decision forest models implementation utilizing automata processors

    公开(公告)号:US11989635B2

    公开(公告)日:2024-05-21

    申请号:US16913582

    申请日:2020-06-26

    CPC classification number: G06N20/20 G06N5/01 G06N20/00

    Abstract: An apparatus includes a processing resource configured to receive a feature vector of a data stream. The feature vector includes a set of feature values. The processing resource is further configured to calculate a set of feature labels based at least in part on the set of feature values to generate a label vector, provide the label vector to another processing resource, and receive a plurality of classifications corresponding to each feature label of the label vector from the other processing resource. The plurality of classifications are generated based at least in part on a respective range of feature values of the set of feature values. The processing resource is configured to then combine the plurality of classifications to generate a final classification of the data stream.

    SPACE EFFICIENT RANDOM FORESTS IMPLEMENTATION UTILIZING AUTOMATA PROCESSORS

    公开(公告)号:US20170255878A1

    公开(公告)日:2017-09-07

    申请号:US15214188

    申请日:2016-07-19

    CPC classification number: G06N20/00 G06N5/003

    Abstract: An apparatus includes a processing resource configured to receive a feature vector of a data stream. The feature vector includes a set of feature values. The processing resource is further configured to calculate a set of feature labels based at least in part on the set of feature values to generate a label vector, provide the label vector to another processing resource, and to receive a plurality of classifications corresponding to each feature label of the label vector from the other processing resource. The plurality of classifications are generated based at least in part on a respective range of feature values of the set of feature values. The processing resource is configured to then combine the plurality of classifications to generate a final classification of the data stream.

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