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CPC Subgroup
G06F 18/211

Selection of the most significant subset of features

Full Title

Pattern recognition > Analysing > Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation > Selection of the most significant subset of features

3 direct subcodes

Child Classifications

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  • G06F 18/2111 by using evolutionary computational techniques, e.g. genetic algorithms
  • G06F 18/2113 by ranking or filtering the set of features, e.g. using a measure of variance or of feature cross-correlation
  • G06F 18/2115 by evaluating different subsets according to an optimisation criterion, e.g. class separability, forward selection or backward elimination

Top Applicants

Top 10 applicants by patent filingsfor class G06, 2013–2023, worldwide · Source: EPO PATSTAT

  1. SAMSUNG ELECTRONICS COMPANY KR 76,952
  2. IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) US 62,841
  3. MICROSOFT TECHNOLOGY LICENSING US 44,778
  4. GOOGLE US 35,735
  5. INTEL CORPORATION US 32,087
  6. HUAWEI TECHNOLOGIES COMPANY CN 30,572
  7. TENCENT TECHNOLOGY (SHENZHEN) COMPANY 25,023
  8. APPLE US 23,482
  9. SGCC(STATE GRID CORPORATION OF CHINA) 22,548
  10. HUAWEI TECHNOLOGIES COMPANY 20,917