Method and system for identifying relevant variables
AssigneeBull SAS
InventorKaoutar SGHIOUER
Life of this patent
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Abstract
The invention relates to a method for identifying variables relevant to a dataset, said variables being derived from a plurality of variables involved in processing the dataset, said method comprising: a step of generating a subset of variables from the plurality of variables, a step of assigning a quantization value to each variable of the generated subset of variables, a step of selecting a relevant variable, a further step of generating a new subset of variables when the quantitative value of the selected variable is below a predetermined threshold value.
Claims15
A method for identifying relevant variables in a dataset including a plurality of data subsets implemented by a computing device, each of the data subsets corresponding to a variable so as to form a set of variables, said method comprising:
- a step of generating a subset of variables from the set of variables, by a variable selection module,
- a step of calculating a performance value for each variable of the generated subset of variables, by the variable selection module,
- a step of selecting at least one relevant variable by applying a genetic algorithm, or by applying selection techniques, and
- a further step of generating a new subset of variables when the performance value of the selected at least one relevant variable is below a predetermined threshold value.
A system for identifying variables relevant to a dataset, implemented by a computing device, said variables being derived from a plurality of variables involved in processing the dataset, said system comprising a variable selection module configured to:
- Generate a subset of variables from the plurality of variables involved in processing the dataset,
- Assign a quantization value to each variable of the generated subset of variables,
- Select a relevant variable by applying a genetic algorithm, or by applying selection techniques, and
- Generate a new subset of variables when the quantitative value of the selected relevant variable is below a predetermined threshold value.
A variable selection module for identifying variables relevant to a dataset, implemented by a computing device, said variables being derived from a plurality of variables involved in processing the dataset, said variable selection module being configured to:
- Generate a subset of variables from the plurality of variables involved in processing the dataset,
- Assign a quantization value to each variable of the generated subset of variables,
- Select a relevant variable by applying a genetic algorithm, or by applying selection techniques, and
- Generate a new subset of variables when the quantitative value of the selected variable is below a predetermined threshold value.
Dependencies are inferred from the claim text.