CN117273887A - Mobile phone bank front-end interface display method, device, equipment and storage medium - Google Patents
Mobile phone bank front-end interface display method, device, equipment and storage medium Download PDFInfo
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Abstract
The application discloses a mobile phone bank front-end interface display method, device, equipment and storage medium, which can be applied to the field of artificial intelligence, the field of big data or the field of finance. Wherein the method comprises the following steps: acquiring a user tag according to the user information; responding to the operation of logging in the mobile phone bank by the user, and displaying an interface corresponding to the user tag to the user at the front end of the mobile phone bank. Based on the user information, when the user logs in the mobile phone bank, an interface corresponding to the user tag is displayed for the user, and accurate recommendation and customized display can be provided for the user, so that the user can first see the interesting content in the process of using the mobile phone bank, the user experience is enhanced, and the user viscosity is increased.
Description
Technical Field
The present disclosure relates to the field of information display technologies, and in particular, to a method, an apparatus, a device, and a storage medium for displaying a front end interface of a mobile phone bank.
Background
At present, when a user logs in a mobile phone bank, a front-end interface of the mobile phone bank displays a plurality of convenient service links, financial product recommendations and hot activity service recommendations, and the interface contents are always uniform, namely, after any user logs in the mobile phone bank, the same recommended contents can be seen. For the user, the recommended contents are not used in a scene, that is, the user does not need the contents, so that the recommendation loses the original meaning, and the user first sees the business which the user wants to transact or the information which the user wants to know in the process of using the mobile phone bank, so that the user experience is poor, and the user viscosity cannot be increased.
Therefore, how to recommend interested contents to different users in the front end interface of the mobile phone bank to enhance the user experience and increase the user viscosity becomes a technical problem to be solved in the field.
Disclosure of Invention
Based on the above problems, the application provides a method, a device, equipment and a storage medium for displaying a front-end interface of a mobile phone bank, which can recommend interested contents to different users in the front-end interface of the mobile phone bank so as to enhance the experience of the users and increase the viscosity of the users.
The embodiment of the application discloses the following technical scheme:
in a first aspect, the present application provides a method for displaying a front-end interface of a mobile banking, where the method includes:
acquiring a user tag according to the user information;
responding to the operation of logging in the mobile phone bank by the user, and displaying an interface corresponding to the user tag to the user at the front end of the mobile phone bank.
Optionally, the obtaining the user tag according to the user information includes:
obtaining a classification learner;
and carrying out automatic marking processing on the user based on the user information by utilizing the classification learner to obtain a user tag corresponding to the user information.
Optionally, the obtaining the classification learner includes:
acquiring a data set containing a plurality of characteristics, wherein the data set contains user information and user labels marked according to the user information;
dividing the data set into a training set and a testing set according to a preset proportion;
performing feature reselection and feature combination on the data in the training set to form a plurality of groups of input features;
using the multiple groups of input features as input, performing data simulation on multiple identical algorithm learners, and obtaining multiple learners through iterative learning; wherein a set of input features can result in a learner;
verifying the prediction effects of the learners by using the test set to obtain a learner with the optimal prediction effect;
taking a group of input features corresponding to the learner with the optimal prediction effect as optimal input features, fitting a model by utilizing the optimal input features, and taking the fitted model as a classification learner; the model is selected according to the optimal input characteristics.
Optionally, in the process of fitting the model using the optimal input feature, the method further includes:
and optimizing the model by using a parameter tuning method.
In a second aspect, an embodiment of the present application provides a mobile banking front-end interface display device, where the device includes:
the user tag acquisition module is used for acquiring a user tag according to the user information;
and the interface display module is used for responding to the operation of logging in the mobile phone bank by the user and displaying the interface corresponding to the user tag to the user at the front end of the mobile phone bank.
Optionally, the user tag obtaining module includes:
the classification learner obtaining sub-module is used for obtaining the classification learner
And the user tag acquisition sub-module is used for automatically marking the user based on the user information by utilizing the classification learner to obtain the user tag corresponding to the user information.
Optionally, the classification learner obtaining sub-module includes:
the data set acquisition unit is used for acquiring a data set containing a plurality of characteristics, wherein the data set contains user information and user labels marked according to the user information;
the data set dividing unit is used for dividing the data set into a training set and a testing set according to a preset proportion;
the input feature acquisition unit is used for carrying out feature reselection and feature combination on the data in the training set to form a plurality of groups of input features;
the learner acquisition unit is used for carrying out data simulation on a plurality of identical algorithm learners by using the plurality of groups of input features as input, and obtaining a plurality of learners through iterative learning; wherein a set of input features can result in a learner;
the learner verification unit is used for verifying the prediction effects of the learners by using the test set to obtain a learner with the optimal prediction effect;
the model fitting unit is used for taking a group of input features corresponding to the learner with the best prediction effect as the best input features, fitting the model by utilizing the best input features, and taking the fitted model as the classification learner; the model is selected according to the optimal input characteristics.
Optionally, the apparatus further includes:
and the model optimization unit is used for optimizing the model by using a parameter tuning method in the process of fitting the model by using the optimal input characteristics.
In a third aspect, an embodiment of the present application provides an electronic device, including:
a memory for storing a computer program;
and the processor is used for realizing the steps of the mobile phone bank front end interface display method when executing the computer program.
In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, where a computer program is stored on the computer readable storage medium, where the computer program when executed by a processor implements the steps of the foregoing method for displaying a front-end interface of a mobile banking.
Compared with the prior art, the application has the following beneficial effects:
the method for displaying the front-end interface of the mobile phone bank comprises the following steps: acquiring a user tag according to the user information; responding to the operation of logging in the mobile phone bank by the user, and displaying an interface corresponding to the user tag to the user at the front end of the mobile phone bank. Based on the user information, when the user logs in the mobile phone bank, an interface corresponding to the user tag is displayed for the user, and accurate recommendation and customized display can be provided for the user, so that the user can first see the interesting content in the process of using the mobile phone bank, the user experience is enhanced, and the user viscosity is increased.
The mobile phone bank front end interface display device, the electronic equipment and the computer readable storage medium provided by the embodiment of the application have the beneficial effects as the steps of the mobile phone bank front end interface display method can be realized.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive faculty for a person skilled in the art.
Fig. 1 is a flow chart of a method for displaying a front-end interface of a mobile phone bank according to an embodiment of the present application;
fig. 2 is a schematic diagram of a front-end interface of a mobile banking machine according to an embodiment of the present application;
fig. 3 is a schematic flow chart of a method for obtaining a classification learner according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a mobile phone bank front end interface display device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
As described above, when a user logs in a mobile phone bank, the front-end interface of the mobile phone bank displays some unified recommended content, and after any user logs in the mobile phone bank, the user can see the same recommended content, and the user first sees the business which the user wants to transact or the information which the user wants to know in the process of using the mobile phone bank, which results in poor user experience and incapability of increasing user viscosity.
Through researches, the inventor invents a mobile phone bank front-end interface display method, device, equipment and storage medium, and can recommend interested contents to different users in the front-end interface of the mobile phone bank so as to enhance user experience and increase user viscosity.
It should be noted that the method, the device, the equipment and the storage medium for displaying the front-end interface of the mobile phone bank provided by the invention can be used in the artificial intelligence field, the big data field or the financial field. The foregoing is merely an example, and the application fields of the method, the device, the equipment and the storage medium for displaying the front-end interface of the mobile phone bank provided by the invention are not limited.
In order to make the present application solution better understood by those skilled in the art, the following description will clearly and completely describe the technical solution in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
Method embodiment
Referring to fig. 1, the flow chart of a mobile phone bank front end interface display method provided by the embodiment of the application includes the following steps:
s101, acquiring a user tag according to the user information.
It should be noted that, in the present application, the user information needs to be obtained through the consent of the user, and the process of obtaining the user information needs to meet the requirements of the related national laws and regulations.
Specifically, the classification learner may be first acquired, and then the user may be automatically marked by using the classification learner based on the user information, to obtain a user tag corresponding to the user information. The labels of the users are acquired through the classification learner, so that user preferences can be determined more accurately, recommended contents which are more interesting for the users can be displayed for the users in the subsequent display process, the users can see the interesting contents in the process of using the mobile phone bank, the user experience is enhanced, and the user viscosity is increased.
Specifically, the user tag can also be obtained through the common service handling frequency in the user information, and the tag corresponding to the common service of the user is used as the user tag.
In the embodiments provided herein, as an example, the user information may include: information such as user age, loan situation, consumption expenditure rate, and common business handling frequency; and the labels of the users can be classified according to the preference condition of the users, for example, the labels of the users can be classified according to the four categories of a convenient service plate, a financial product recommendation plate, a bank information plate and a preferential activity plate. Specifically, the convenient service plate can mark the user according to the common service of the user, and the labels are classified into a foreign currency service class, a life service class, a credit card service class and the like; the financial product recommendation plate can divide the labels into cash categories, robust categories, advanced categories and the like; the bank information blocks can be classified into "" cross-border information, "" fund information, "" noble metal information ""; the preferential activity plates can be divided into labels such as communication, catering, traffic and the like. The label dividing mode is that the embodiment provided by the application divides the display of the front end of the mobile phone bank into four large plates, namely the convenient business link plate, the financial product recommending plate, the bank information plate and the preferential activity plate, and particularly can be seen in fig. 2, which is a schematic diagram of the front end interface of the mobile phone bank provided by the embodiment of the application, the front end interface of the mobile phone bank APP displays the four large plates, and recommended contents can be displayed on the four large plates.
S102, responding to the operation of logging in the mobile phone bank by the user, and displaying an interface corresponding to the user tag to the user at the front end of the mobile phone bank.
When a user logs in the mobile phone bank, the front end of the mobile phone bank displays a corresponding interface according to the label of the user, so that the user can first see the interested contents in the process of using the mobile phone bank, thereby enhancing the experience of the user and increasing the viscosity of the user.
According to the mobile phone bank front-end interface display method, the user label is obtained according to the user information; responding to the operation of logging in the mobile phone bank by the user, and displaying an interface corresponding to the user tag to the user at the front end of the mobile phone bank. Based on the user information, when the user logs in the mobile phone bank, an interface corresponding to the user tag is displayed for the user, and accurate recommendation and customized display can be provided for the user, so that the user can first see the interesting content in the process of using the mobile phone bank, the user experience is enhanced, and the user viscosity is increased.
For better understanding of the present application, the embodiment of the present application further provides a method for obtaining a class learner, referring to fig. 3, which is a schematic flow chart of a method for obtaining a class learner according to the embodiment of the present application, including the following steps:
s301, acquiring a data set containing a plurality of features, wherein the data set contains user information and user labels marked according to the user information.
It should be noted that, in step S301, a portion of the data set may be selected, where the portion of the data set includes user information such as user age, loan situation, consumption expense ratio, and frequency of handling the common business, and the users in the portion of the data set may be marked manually according to the user information, that is, user labels are given to the users, and the user labels may be classified into "foreign currency business class", "life service class", "credit card business class", and so on.
S302, dividing the data set into a training set and a testing set according to a preset proportion.
Specifically, the preset proportion may be set according to the actual situation, for example, 80% of the training set may be used as the training set, the remaining 20% may be used as the test set, or 85% of the training set may be used as the training set, and the remaining 15% may be used as the test set.
S303, performing feature reselection and feature combination on the data in the training set to form a plurality of groups of input features.
It can be understood that the training set includes a plurality of features, that is, user information and user labels corresponding to each user, and features are reselected and combined with different features, that is, the user information and the user labels are recombined to form a plurality of groups of input features, which can be denoted as a1, a2, a3 … an.
S304, using the multiple groups of input features as input, performing data simulation on multiple identical algorithm learners, and obtaining multiple learners through iterative learning; wherein a set of input features can result in a learner.
In step S304, the plurality of sets of input features generated in step S303 are used as inputs, data simulation is performed using the same algorithm learner, and a plurality of learners, denoted by b1, b2, and b3 … bn, can be generated through iterative learning. The learner obtained by using the a1 group input feature is b1, the learner obtained by using the a2 group input feature is b2, the learner obtained by using the a3 group input feature is b3, and the learner obtained by using the an group input feature is bn.
And S305, verifying the prediction effects of the learners by using the test set to obtain the learner with the optimal prediction effect.
In step S302, the data set has been divided into a training set and a test set, and it can be understood that the test set includes user information of a plurality of users and user labels corresponding to the user information, and the user information in the test set is used to predict the user information by using the plurality of learners obtained in step S304, and whether the prediction result is consistent with the user label corresponding to the user information or not is verified, so that how the learner predicts the effect can be known, and therefore, a learner with the best prediction effect can be selected from the plurality of learners.
S306, using a group of input features corresponding to the learner with the best prediction effect as the best input features, fitting the model by using the best input features, and using the fitted model as a classification learner; the model is selected according to the optimal input characteristics.
It can be understood that, since each learner has a one-to-one correspondence with one set of input features, it can be confirmed which set of input features corresponds to the learner with the best prediction effect, for example, b1 corresponds to the learner with the best prediction effect, and then the corresponding input features are labeled as a1; for another example, where the learner with the best prediction is bn, the corresponding input feature is numbered an.
It should be noted that, in the embodiment provided in the present application, since each set of input features is different, in step S306, when the model is fitted by using the best input feature, the selected model is selected based on the best input feature, for example, models c1, c2 and c3 exist, and when the best input feature is a1, the effect of fitting it by using the model c1 is better, and then the model c1 is selected for fitting at this time; when the optimal input feature is a2, the effect of fitting the optimal input feature by using the model c2 is better, and then the model c2 is selected for fitting.
According to the method for obtaining the classification learner, a data set containing a plurality of characteristics is obtained, and the data set contains user information and user labels marked according to the user information; dividing the data set into a training set and a testing set according to a preset proportion; performing feature reselection and feature combination on the data in the training set to form a plurality of groups of input features; using the multiple groups of input features as input, performing data simulation on multiple identical algorithm learners, and obtaining multiple learners through iterative learning; wherein a set of input features can result in a learner; verifying the prediction effects of the learners by using the test set to obtain a learner with the optimal prediction effect; and taking a group of input features corresponding to the learner with the optimal prediction effect as optimal input features, fitting the model by utilizing the optimal input features, and taking the fitted model as a classification learner. The method comprises the steps that a plurality of learners are obtained based on a plurality of groups of data, optimal data corresponding to the optimal learners are obtained through verifying the effects of the learners, and the classification learners obtained by utilizing the optimal data can obtain user labels based on user information more accurately, so that interesting contents of the learners can be recommended to users more accurately, the users can see the interesting contents of the learners in the process of using a mobile phone bank, user experience is enhanced, and user viscosity is increased.
It should be noted that, in the embodiment provided in the present application, in the process of fitting the model by using the optimal input feature, the model may also be optimized by using a parameter tuning method. The model is optimized in a parameter tuning mode, so that a classification learner with better prediction effect can be obtained, and the classification learner is more accurate when used for classifying the user labels based on the user information, so that the content which is more in line with the preference of the user can be recommended to the user, the user can see the interesting content in the process of using the mobile phone bank, the user experience is enhanced, and the user viscosity is increased.
The embodiment of the application also provides a mobile phone bank front-end interface display method, which can divide the display of the mobile phone bank front end into four modules, namely a convenient service link module, a financial product recommendation module, a bank information module and a preferential activity module. For the display content of each module, the labels of the users can be classified according to the preference condition of the users, for example, the convenient service module marks the users according to the common service of the users, and the labels are classified into foreign currency service class, life service class, credit card service class and the like; the financial product recommendation module can divide the labels into cash categories, robust categories, advanced categories and the like; the bank information module can be divided into "" cross-border information, "" foundation information, "" precious metal information ""; the preferential activity module can be divided into labels of communication, catering, traffic and the like. And selecting a proper algorithm model by using user information in a bank database, such as user age, loan situation, consumption expenditure ratio, common business handling frequency and the like, as training data, so that the model performs data learning. Aiming at four modules at the front end of a mobile phone bank, different input features are respectively combined or reconstructed to serve as the input features of a model, the model is trained, and the model with the best final effect is used as a learner for distinguishing user labels. After the learner is obtained, the user label can be judged, if the user label is 'foreign currency business type' + 'robust type' + 'cross-border information' + 'traffic type', the front-end intelligent display can be carried out on the user, when the user logs in the mobile phone bank, the convenient business module displays a plurality of foreign currency related business transaction links, the financial product recommending module recommends robust financial products with smaller risks, the information module recommends cross-border financial related information, and the preferential activity module recommends preferential activities related to the transportation trip.
Device embodiment
Referring to fig. 4, the structure of a front-end interface display device for a mobile phone bank according to an embodiment of the present application includes: the user tag acquisition module 401 and the interface presentation module 402.
The user tag obtaining module 401 is configured to obtain a user tag according to user information;
the interface display module 402 is configured to display an interface corresponding to the user tag to the user at the front end of the mobile phone bank in response to an operation of the user logging in the mobile phone bank.
Optionally, the user tag obtaining module 401 includes:
the classification learner obtaining sub-module is used for obtaining the classification learner
And the user tag acquisition sub-module is used for automatically marking the user based on the user information by utilizing the classification learner to obtain the user tag corresponding to the user information.
Optionally, the classification learner obtaining sub-module includes:
the data set acquisition unit is used for acquiring a data set containing a plurality of characteristics, wherein the data set contains user information and user labels marked according to the user information;
the data set dividing unit is used for dividing the data set into a training set and a testing set according to a preset proportion;
the input feature acquisition unit is used for carrying out feature reselection and feature combination on the data in the training set to form a plurality of groups of input features;
the learner acquisition unit is used for carrying out data simulation on a plurality of identical algorithm learners by using the plurality of groups of input features as input, and obtaining a plurality of learners through iterative learning; wherein a set of input features can result in a learner;
the learner verification unit is used for verifying the prediction effects of the learners by using the test set to obtain a learner with the optimal prediction effect;
and the model fitting unit is used for taking a group of input features corresponding to the learner with the best prediction effect as the best input features, fitting the model by utilizing the best input features, and taking the fitted model as the classification learner.
Optionally, the apparatus further includes:
and the model optimization unit is used for optimizing the model by using a parameter tuning method in the process of fitting the model by using the optimal input characteristics.
According to the mobile phone bank front-end interface display device, the user tag is obtained according to the user information by utilizing the user tag obtaining module and the interface display module; responding to the operation of logging in the mobile phone bank by the user, and displaying an interface corresponding to the user tag to the user at the front end of the mobile phone bank. Based on the user information, when the user logs in the mobile phone bank, an interface corresponding to the user tag is displayed for the user, and accurate recommendation and customized display can be provided for the user, so that the user can first see the interesting content in the process of using the mobile phone bank, the user experience is enhanced, and the user viscosity is increased.
Electronic equipment is realExamples
Referring to fig. 5, the schematic structural diagram of an electronic device provided in an embodiment of the present application includes:
a memory 11 for storing a computer program;
and the processor 12 is configured to implement the steps of the mobile banking front-end interface display method according to any of the method embodiments when executing the computer program.
In this embodiment, the device may be a vehicle-mounted computer, a PC (Personal Computer ), or a terminal device such as a smart phone, a tablet computer, a palm computer, or a portable computer.
The device may include a memory 11, a processor 12, and a bus 13.
The memory 11 includes at least one type of readable storage medium including flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the device, such as a hard disk of the device. The memory 11 may in other embodiments also be an external storage device of the device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the device. Further, the memory 11 may also include both an internal storage unit of the device and an external storage device. The memory 11 may be used not only for storing application software installed in the device and various data such as program codes for executing a mobile banking front-end interface presentation method, but also for temporarily storing data that has been output or is to be output.
The processor 12 may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor or other data processing chip in some embodiments for running program code or processing data stored in the memory 11, such as program code for performing a mobile banking front-end interface presentation method, etc.
The bus 13 may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus, or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in fig. 5, but not only one bus or one type of bus.
Further, the device may also include a network interface 14, and the network interface 14 may optionally include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the device and other electronic devices.
Optionally, the device may further comprise a user interface 15, the user interface 15 may comprise a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 15 may further comprise a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the device and for displaying a visual user interface.
Fig. 5 shows only a device having components 11-15, it will be understood by those skilled in the art that the configuration shown in fig. 5 is not limiting of the device and may include fewer or more components than shown, or may combine certain components, or a different arrangement of components.
Readable storage medium embodiments
The embodiment of the application also provides a computer readable storage medium, and the computer readable storage medium stores a computer program, and the computer program realizes the steps of the mobile phone bank front end interface display method according to any of the method embodiments when being executed by a processor.
Wherein the storage medium may include: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
It should be noted that, in the present specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment is mainly described in a different point from other embodiments. In particular, for apparatus, electronic devices, and readable storage medium embodiments, since they are substantially similar to method embodiments, the description is simpler, and relevant points are found in the partial description of method embodiments. The apparatus, electronic device, and readable storage medium embodiments described above are merely illustrative, where modules illustrated as separate components may or may not be physically separate, and components that are hinted by modules may or may not be physical units, may be located in one place, or may be distributed over multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The foregoing is merely one specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. The mobile phone bank front-end interface display method is characterized by comprising the following steps:
acquiring a user tag according to the user information;
responding to the operation of logging in the mobile phone bank by the user, and displaying an interface corresponding to the user tag to the user at the front end of the mobile phone bank.
2. The method of claim 1, wherein the obtaining the user tag based on the user information comprises:
obtaining a classification learner;
and carrying out automatic marking processing on the user based on the user information by utilizing the classification learner to obtain a user tag corresponding to the user information.
3. The method of claim 2, wherein the acquiring a class learner comprises:
acquiring a data set containing a plurality of characteristics, wherein the data set contains user information and user labels marked according to the user information;
dividing the data set into a training set and a testing set according to a preset proportion;
performing feature reselection and feature combination on the data in the training set to form a plurality of groups of input features;
using the multiple groups of input features as input, performing data simulation on multiple identical algorithm learners, and obtaining multiple learners through iterative learning; wherein a set of input features can result in a learner;
verifying the prediction effects of the learners by using the test set to obtain a learner with the optimal prediction effect;
taking a group of input features corresponding to the learner with the optimal prediction effect as optimal input features, fitting a model by utilizing the optimal input features, and taking the fitted model as a classification learner; the model is selected according to the optimal input characteristics.
4. A method according to claim 3, wherein during said fitting of the model with said optimal input features, the method further comprises:
and optimizing the model by using a parameter tuning method.
5. A mobile banking front-end interface display device, characterized in that the device comprises:
the user tag acquisition module is used for acquiring a user tag according to the user information;
and the interface display module is used for responding to the operation of logging in the mobile phone bank by the user and displaying the interface corresponding to the user tag to the user at the front end of the mobile phone bank.
6. The apparatus of claim 5, wherein the user tag acquisition module comprises:
the classification learner obtaining sub-module is used for obtaining the classification learner
And the user tag acquisition sub-module is used for automatically marking the user based on the user information by utilizing the classification learner to obtain the user tag corresponding to the user information.
7. The apparatus of claim 6, wherein the class learner acquisition sub-module comprises:
the data set acquisition unit is used for acquiring a data set containing a plurality of characteristics, wherein the data set contains user information and user labels marked according to the user information;
the data set dividing unit is used for dividing the data set into a training set and a testing set according to a preset proportion;
the input feature acquisition unit is used for carrying out feature reselection and feature combination on the data in the training set to form a plurality of groups of input features;
the learner acquisition unit is used for carrying out data simulation on a plurality of identical algorithm learners by using the plurality of groups of input features as input, and obtaining a plurality of learners through iterative learning; wherein a set of input features can result in a learner;
the learner verification unit is used for verifying the prediction effects of the learners by using the test set to obtain a learner with the optimal prediction effect;
the model fitting unit is used for taking a group of input features corresponding to the learner with the best prediction effect as the best input features, fitting the model by utilizing the best input features, and taking the fitted model as the classification learner; the model is selected according to the optimal input characteristics.
8. The apparatus of claim 7, wherein the apparatus further comprises:
and the model optimization unit is used for optimizing the model by using a parameter tuning method in the process of fitting the model by using the optimal input characteristics.
9. An electronic device, comprising:
a memory for storing a computer program;
a processor, configured to implement the steps of the mobile banking front-end interface display method according to any one of claims 1 to 4 when executing the computer program.
10. A computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and when executed by a processor, the computer program implements the steps of the mobile banking front-end interface presentation method as claimed in any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311212492.6A CN117273887A (en) | 2023-09-20 | 2023-09-20 | Mobile phone bank front-end interface display method, device, equipment and storage medium |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202311212492.6A CN117273887A (en) | 2023-09-20 | 2023-09-20 | Mobile phone bank front-end interface display method, device, equipment and storage medium |
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| CN202311212492.6A Pending CN117273887A (en) | 2023-09-20 | 2023-09-20 | Mobile phone bank front-end interface display method, device, equipment and storage medium |
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| CN (1) | CN117273887A (en) |
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