CN112836741A - Crowd sketch extraction method, system, equipment and computer readable medium for coupling decision tree - Google Patents
Crowd sketch extraction method, system, equipment and computer readable medium for coupling decision tree Download PDFInfo
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Abstract
The invention discloses a crowd sketch extracting method, a system, equipment and a computer readable medium of a coupled decision tree, wherein the crowd sketch extracting method comprises the following steps: a decision tree generation step of randomly generating a decision tree from a given data set and a variable space; a characteristic extraction step, namely extracting a regular path in each decision tree, and the hit rate, the target variable response rate and the target variable mean value of each intermediate node and leaf node; simultaneously outputting the repeated use number and the high-frequency interval of each variable in the characteristic space; and a crowd sketch generation step, namely completely and automatically extracting target crowds according to the business requirements of the user and inducing the crowd sketch. The method can completely and automatically extract the target crowd according to the business requirements of the user and induce the crowd portrait; compared with an empirical method, the method can accommodate more characteristic spaces and give consideration to certain interpretability, and has universal value in the fields of financial wind control, data operation and the like.
Description
Technical Field
The invention belongs to the technical field of information extraction, and relates to a crowd sketch extraction system, in particular to a crowd sketch extraction method, a system, equipment and a computer readable medium coupled with a decision tree.
Background
The existing rule method based on the decision tree needs to manually search the rules from the decision tree, the information of the middle node cannot be acquired, and a lot of useful crowd portrait rules can be lost. Meanwhile, the candidate rule set cannot be searched from a large number of feature spaces in batch. There is a need for a method that combines the effects and efficiency of rule generation.
In view of the above, there is a need to design a new people portrait extraction method to overcome at least some of the above-mentioned defects of the existing people portrait extraction methods.
Disclosure of Invention
The invention provides a crowd sketch extracting method, a system, equipment and a computer readable medium coupled with a decision tree, which can completely and automatically extract target crowds according to user business requirements and induce the crowd sketch.
In order to solve the technical problem, according to one aspect of the present invention, the following technical solutions are adopted:
a crowd portrayal extraction method coupled with a decision tree comprises the following steps:
a decision tree generation step, namely, opening user-defined parameters to prevent rule overfitting and randomly generating a preselected set of a decision tree from a given data set and a given variable space according to rule complexity requirements and rule confidence requirements input by a user;
a characteristic extraction step, namely traversing each decision tree in the preselection set, and extracting paths reaching each intermediate node and each leaf node in the decision trees, wherein path tracks are rules; at least one of the hit rate, the target variable response rate and the target variable mean value of the rule is recorded; simultaneously outputting the repeated use number and the high-frequency interval of each variable in the characteristic space; the target variable response rate corresponds to a two-class and multi-class problem, and the target variable mean value corresponds to a regression problem;
a crowd sketch generation step, namely completely and automatically extracting target crowds according to the business requirements of users and summarizing the crowd sketch; generating a report of all rules on a sample set of user inputs; the method comprises at least one of crowd hit rate, target variable response rate, target variable mean value and promotion rate of rules on response crowd, and can count the complaint index according to user-defined dimension clustering; meanwhile, the portrait generator gives an importance list of the variables and a high-frequency use area of each variable; the user can obtain the crowd commonality from the output report.
According to another aspect of the invention, the following technical scheme is adopted: a crowd portrayal extraction method coupled with a decision tree comprises the following steps:
a decision tree generation step of randomly generating a preselected set of decision trees from a given data set and a variable space;
a characteristic extraction step, namely extracting characteristic data in the decision tree;
and a crowd sketch generation step, namely completely and automatically extracting target crowds according to the business requirements of the user and inducing the crowd sketch.
In one embodiment of the present invention, in the decision tree generating step, according to the rule complexity requirement and the rule confidence requirement input by the user, and opening the user-defined parameter to prevent rule overfitting,
as an embodiment of the present invention, in the feature extraction step, each decision tree in the preselection set is traversed, a path reaching each intermediate node and each leaf node in the decision tree is extracted, and a path trajectory is a rule; at least one of the hit rate, the target variable response rate and the target variable mean value of the rule is recorded; simultaneously outputting the repeated use number and the high-frequency interval of each variable in the characteristic space; the target variable response rate corresponds to a two-class and multi-class problem, and the target variable mean value corresponds to a regression problem; the target variable response rate corresponds to a two-class and multi-class problem, and the target variable mean value corresponds to a regression problem.
In one embodiment of the present invention, the crowd sketch generating step generates a report of all rules on a sample set input by a user; the method comprises at least one of crowd hit rate, target variable response rate, target variable mean value and promotion rate of rules on response crowd, and can count the complaint index according to user-defined dimension clustering; meanwhile, the portrait generator gives an importance list of the variables and a high-frequency use area of each variable; the user can obtain the crowd commonality from the output report.
According to another aspect of the invention, the following technical scheme is adopted: a crowd portrayal extraction system coupled to a decision tree, the crowd portrayal extraction system comprising:
the decision tree generation module is used for randomly generating a preselected set of a decision tree according to a rule complexity requirement and a rule confidence requirement input by a user in a given data set and a variable space and by opening user-defined parameters to prevent rule overfitting;
the characteristic extraction module is used for traversing each decision tree in the preselection set and extracting paths reaching each intermediate node and each leaf node in the decision trees, wherein the path tracks are rules; at least one of the hit rate, the target variable response rate and the target variable mean value of the rule is recorded; simultaneously outputting the repeated use number and the high-frequency interval of each variable in the characteristic space;
the crowd image generation module is used for completely and automatically extracting target crowds according to the business requirements of users and inducing crowd images; generating a report of all rules on a sample set of user inputs; the method comprises at least one of crowd hit rate, target variable response rate, target variable mean value and promotion rate of rules on response crowd, and can count the complaint index according to user-defined dimension clustering; meanwhile, the portrait generator gives an importance list of the variables and a high-frequency use area of each variable; the user can obtain the crowd commonality from the output report.
As an embodiment of the present invention, the target variable response rate corresponds to a two-class or multi-class problem, and the target variable mean corresponds to a regression problem.
According to another aspect of the invention, the following technical scheme is adopted: a crowd portrayal extraction system coupled to a decision tree, the crowd portrayal extraction system comprising:
a decision tree generation module for randomly generating a preselected set of decision trees from a given data set, variable space;
the characteristic extraction module is used for extracting characteristic data in the decision tree; and
and the crowd image generation module is used for completely and automatically extracting the target crowd according to the business requirements of the user and inducing the crowd image.
According to another aspect of the invention, the following technical scheme is adopted: apparatus for a people profile extraction method, the apparatus comprising a memory for storing computer program instructions and a processor for executing the computer program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform the method.
According to another aspect of the invention, the following technical scheme is adopted: a computer readable medium having stored thereon computer program instructions executable by a processor to implement the above-described method.
The invention has the beneficial effects that: the crowd sketch extracting method, the system, the equipment and the computer readable medium of the coupled decision tree can completely and automatically extract target crowds according to the business requirements of users and induce the crowd sketch; compared with an empirical method, the method can accommodate more characteristic spaces and give consideration to certain interpretability, and has universal value in the fields of financial wind control, data operation and the like.
Drawings
FIG. 1 is a flowchart illustrating a crowd sketch extracting method according to an embodiment of the present invention.
FIG. 2 is a schematic diagram of a crowd sketch extracting system according to an embodiment of the invention.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
For a further understanding of the invention, reference will now be made to the preferred embodiments of the invention by way of example, and it is to be understood that the description is intended to further illustrate features and advantages of the invention, and not to limit the scope of the claims.
The description in this section is for several exemplary embodiments only, and the present invention is not limited only to the scope of the embodiments described. It is within the scope of the present disclosure and protection that the same or similar prior art means and some features of the embodiments may be interchanged.
The steps in the embodiments in the specification are only expressed for convenience of description, and the implementation manner of the present application is not limited by the order of implementation of the steps. The term "connected" in the specification includes both direct connection and indirect connection.
The invention discloses a crowd sketch extracting method of a coupling decision tree, and FIG. 1 is a flow chart of the crowd sketch extracting method in an embodiment of the invention; referring to fig. 1, the method for extracting a people portrait includes:
step S1 is a decision tree generation step of randomly generating a preselected set of decision trees from a given data set and variable space.
In one embodiment, a preselected set of decision trees is randomly generated from a given data set, variable space, according to a rule complexity requirement, a rule confidence requirement, and open user-defined parameters that prevent rule overfitting entered by a user.
Step S2, feature extraction, which extracts feature data in the decision tree.
In an embodiment of the invention, each decision tree in the preselection set is traversed, a path reaching each intermediate node and each leaf node in the decision tree is extracted, and a path track is a rule; at least one of the hit rate, the target variable response rate and the target variable mean value of the rule is recorded; and simultaneously outputting the repeated use number and the high-frequency interval of each variable in the feature space. In one embodiment, the target variable response rate corresponds to a two-class or multi-class problem, and the target variable mean corresponds to a regression problem.
Step S3, a crowd sketch generation step of automatically extracting the target crowd according to the user business demand and summarizing the crowd sketch.
In one embodiment, a report of all rules is generated on a sample set of user inputs; the method comprises at least one of crowd hit rate, target variable response rate, target variable mean value and promotion rate of rules on response crowd, and can count the complaint index according to user-defined dimension clustering; meanwhile, the portrait generator gives an importance list of the variables and a high-frequency use area of each variable; the user can obtain the crowd commonality from the output report.
The invention also discloses a crowd sketch extracting system coupled with the decision tree, and FIG. 2 is a schematic composition diagram of the crowd sketch extracting system in an embodiment of the invention; referring to fig. 2, the crowd sketch extracting system includes: a decision tree generating module 1, a feature extracting module 2 and a crowd sketch generating module 3.
The decision tree generation module 1 is used to randomly generate a preselected set of decision trees from a given data set, variable space. In one embodiment, the preselected set of decision trees may be randomly generated based on a rule complexity requirement, a rule confidence requirement, and user-defined parameters that are input by a user to prevent rule overfitting.
The feature extraction module 2 is used for extracting feature data in the decision tree. In an embodiment of the invention, each decision tree in the preselection set is traversed, a path reaching each intermediate node and each leaf node in the decision tree is extracted, and a path track is a rule; at least one of the hit rate, the target variable response rate and the target variable mean value of the rule is recorded; and simultaneously outputting the repeated use number and the high-frequency interval of each variable in the feature space. In one embodiment, the target variable response rate corresponds to a two-class or multi-class problem, and the target variable mean corresponds to a regression problem.
The crowd image generation module 3 is used for completely and automatically extracting target crowd according to the business requirements of users and inducing the crowd image. In one embodiment, a report of all rules is generated on a sample set of user inputs; the method comprises at least one of crowd hit rate, target variable response rate, target variable mean value and promotion rate of rules on response crowd, and can count the complaint index according to user-defined dimension clustering; meanwhile, the portrait generator gives an importance list of the variables and a high-frequency use area of each variable; the user can obtain the crowd commonality from the output report.
The invention also discloses a device of the crowd image extraction method, the device comprises a memory for storing computer program instructions and a processor for executing the computer program instructions, wherein when the computer program instructions are executed by the processor, the device is triggered to execute the method.
The invention further discloses a computer readable medium having stored thereon computer program instructions executable by a processor to implement the above-described method.
In summary, the crowd sketch extracting method, system, device and computer readable medium of the coupled decision tree provided by the invention can completely and automatically extract the target crowd according to the business requirements of the user and induce the crowd sketch; compared with an empirical method, the method can accommodate more characteristic spaces and give consideration to certain interpretability, and has universal value in the fields of financial wind control, data operation and the like.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware; for example, it may be implemented using Application Specific Integrated Circuits (ASICs), general purpose computers, or any other similar hardware devices. In some embodiments, the software programs of the present application may be executed by a processor to implement the above steps or functions. As such, the software programs (including associated data structures) of the present application can be stored in a computer-readable recording medium; such as RAM memory, magnetic or optical drives or diskettes, and the like. In addition, some steps or functions of the present application may be implemented using hardware; for example, as circuitry that cooperates with the processor to perform various steps or functions.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The description and applications of the invention herein are illustrative and are not intended to limit the scope of the invention to the embodiments described above. Effects or advantages referred to in the embodiments may not be reflected in the embodiments due to interference of various factors, and the description of the effects or advantages is not intended to limit the embodiments. Variations and modifications of the embodiments disclosed herein are possible, and alternative and equivalent various components of the embodiments will be apparent to those skilled in the art. It will be clear to those skilled in the art that the present invention may be embodied in other forms, structures, arrangements, proportions, and with other components, materials, and parts, without departing from the spirit or essential characteristics thereof. Other variations and modifications of the embodiments disclosed herein may be made without departing from the scope and spirit of the invention.
Claims (10)
1. A crowd sketch extracting method coupled with a decision tree is characterized by comprising the following steps:
a decision tree generation step, namely, opening user-defined parameters to prevent rule overfitting and randomly generating a preselected set of a decision tree from a given data set and a given variable space according to rule complexity requirements and rule confidence requirements input by a user;
a characteristic extraction step, namely traversing each decision tree in the preselection set, and extracting paths reaching each intermediate node and each leaf node in the decision trees, wherein path tracks are rules; recording at least one of the hit rate, the target variable response rate and the target variable mean value of the rule; simultaneously outputting the repeated use number and the high-frequency interval of each variable in the characteristic space; the target variable response rate corresponds to a two-class and multi-class problem, and the target variable mean value corresponds to a regression problem;
a crowd sketch generation step, namely completely and automatically extracting target crowds according to the business requirements of users and summarizing the crowd sketch; generating a report of all rules on a sample set of user inputs; the method comprises at least one of crowd hit rate, target variable response rate, target variable mean value and promotion rate of rules on response crowd, and can count the complaint index according to user-defined dimension clustering; meanwhile, the portrait generator gives an importance list of the variables and a high-frequency use area of each variable; the user can obtain the crowd commonality from the output report.
2. A crowd sketch extracting method coupled with a decision tree is characterized by comprising the following steps:
a decision tree generation step of randomly generating a preselected set of decision trees from a given data set and a variable space;
a characteristic extraction step, namely extracting characteristic data in the decision tree;
and a crowd sketch generation step, namely completely and automatically extracting target crowds according to the business requirements of the user and inducing the crowd sketch.
3. The method of claim 2, wherein the method comprises:
and in the decision tree generating step, according to the rule complexity requirement and the rule confidence requirement input by the user, user-defined parameters are opened to prevent rule overfitting.
4. The method of claim 2, wherein the method comprises:
in the characteristic extraction step, traversing each decision tree in the preselection set, and extracting paths reaching each intermediate node and each leaf node in the decision trees, wherein path tracks are rules; at least one of the hit rate, the target variable response rate and the target variable mean value of the rule is recorded; simultaneously outputting the repeated use number and the high-frequency interval of each variable in the characteristic space; the target variable response rate corresponds to a two-class and multi-class problem, and the target variable mean value corresponds to a regression problem; the target variable response rate corresponds to a two-class and multi-class problem, and the target variable mean value corresponds to a regression problem.
5. The method of claim 2, wherein the method comprises:
in the step of generating the crowd sketch, all regular reports are generated on a sample set input by a user; the method comprises at least one of crowd hit rate, target variable response rate, target variable mean value and promotion rate of rules on response crowd, and can count the complaint index according to user-defined dimension clustering; meanwhile, the portrait generator gives an importance list of the variables and a high-frequency use area of each variable; the user can obtain the crowd commonality from the output report.
6. A crowd portrayal extraction system coupled to a decision tree, the crowd portrayal extraction system comprising:
the decision tree generation module is used for randomly generating a preselected set of a decision tree according to a rule complexity requirement and a rule confidence requirement input by a user in a given data set and a variable space and by opening user-defined parameters to prevent rule overfitting;
the characteristic extraction module is used for traversing each decision tree in the preselection set and extracting paths reaching each intermediate node and each leaf node in the decision trees, wherein the path tracks are rules; at least one of the hit rate, the target variable response rate and the target variable mean value of the rule is recorded; simultaneously outputting the repeated use number and the high-frequency interval of each variable in the characteristic space;
the crowd image generation module is used for completely and automatically extracting target crowds according to the business requirements of users and inducing crowd images; generating a report of all rules on a sample set of user inputs; the method comprises at least one of crowd hit rate, target variable response rate, target variable mean value and promotion rate of rules on response crowd, and can count the complaint index according to user-defined dimension clustering; meanwhile, the portrait generator gives an importance list of the variables and a high-frequency use area of each variable; the user can obtain the crowd commonality from the output report.
7. The decision tree coupled people representation extraction system of claim 6, wherein:
the target variable response rate corresponds to a two-class and multi-class problem, and the target variable mean value corresponds to a regression problem.
8. A crowd portrayal extraction system coupled to a decision tree, the crowd portrayal extraction system comprising:
a decision tree generation module for randomly generating a preselected set of decision trees from a given data set, variable space;
the characteristic extraction module is used for extracting characteristic data in the decision tree; and
and the crowd image generation module is used for completely and automatically extracting the target crowd according to the business requirements of the user and inducing the crowd image.
9. An apparatus for a people profile extraction method, the apparatus comprising a memory for storing computer program instructions and a processor for executing the computer program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform the method of any one of claims 1 to 5.
10. A computer-readable medium having computer program instructions stored thereon, the computer-readable instructions being executable by a processor to implement the method of any one of claims 1 to 5.
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