CN108021535A - Data fitting method and device - Google Patents
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Abstract
The invention discloses a kind of data fitting method and device.Wherein, this method includes：Fitting data is treated in acquisition；Fitting data is treated using selected at least one fitting function to be fitted, and obtains at least one fitting result；According to the corresponding goodness of fit of each fitting result, multiple fitting results are screened.The present invention solves data fitting in the prior art according to the low technical problem of the efficiency that artificial experience selects fitting function to cause data to be fitted.
Description
Technical field
The present invention relates to computer realm, in particular to a kind of data fitting method and device.
Background technology
In big data epoch, either new media or internet, substantial amounts of user and enormous amount have been directed to
Data.How these data are carried out it is rationally effective utilize, allow production, the service for life that data really can be for us, this
Will be when we face mass data need in face of the problem of.
In order to preferably being found using big data with, it is necessary to be concerned about by big data between two, or multiple variables
Certain dependency relation, and in this, as reference and instruct, so as to be used, further promote and influence our work and
Life.When two groups of data are fitted, suitable fitting function is selected just to make to treat that fitting data is preferably fitted,
Degree of fitting with higher.
All it is manually empirically or random manner selection fitting function, to be modeled sum number for existing technology
According to fitting.When in face of two groups or it is multigroup be not familiar with its property data when, the method that can only use random guess is artificial
The one or more of fitting functions of selection, are fitted experiment.It is this by the method for the selection of fitting function manually carried out, be
It is a kind of to repeat the higher work of degree, very labor intensive and time.When selecting fitting function, if the fitting of selection very little
Function, may result in that selected fitting function is improper, be unable to reach the higher goodness of fit；If the more fitting letter of selection
Number, it is necessary to the artificial experiment of fitting repeatedly, cumbersome and labor intensive.For example, according to preset data characteristic, fitting data will be treated
The data of concentration are divided into n groups and treat fitting data, n >=2；The number to be fitted for meeting default fitting condition in fitting data is treated to n groups
According to being fitted to obtain k fitting function, 1≤k≤n；Final fitting function is obtained, final fitting function is k fitting function
Product.
It is low according to the efficiency that artificial experience selects fitting function to cause data to be fitted for the fitting of data in the prior art
Problem, not yet proposes effective solution at present.
The content of the invention
An embodiment of the present invention provides a kind of data fitting method and device, at least to solve data fitting in the prior art
Fitting function is selected to cause the low technical problem of the efficiency of data fitting according to artificial experience.
One side according to embodiments of the present invention, there is provided a kind of data fitting method, including：Obtain number to be fitted
According to；Treat that fitting data is fitted to described using selected at least one fitting function, obtain at least one fitting result；Root
According to the corresponding goodness of fit of each fitting result, multiple fitting results are screened.
Further, start multiple threads fitting data is treated by selected at least one fitting function respectively and intended
Close, obtain at least one fitting result.
Further, the corresponding goodness of fit of each fitting result is calculated；It is excellent that fitting is filtered out from multiple fitting results
Highest fitting result is spent, as final fitting result.
Further, in the case where selected fitting function is a fitting function, if having multiple numbers to be fitted
According to then starting multiple threads by a selected fitting function while treat that fitting data is fitted to multiple.
Further, selected at least one fitting function includes：Linear fit function, polynomial fit function, index
Fitting function and logistic fit function.
Another aspect according to embodiments of the present invention, additionally provides a kind of data fitting device, including：First obtains mould
Block, fitting data is treated for obtaining；Second acquisition module, for treating fitting data using selected at least one fitting function
It is fitted, obtains at least one fitting result；Screening module is right for according to the corresponding goodness of fit of each fitting result
Multiple fitting results are screened.
Further, promoter module, for starting multiple threads respectively by selected at least one fitting function pair
Treat that fitting data is fitted, obtain at least one fitting result.
Further, in the case where selected fitting function is a fitting function, if having multiple numbers to be fitted
According to then starting multiple threads by a selected fitting function while treat that fitting data is fitted to multiple.
Further, selected at least one fitting function includes：Linear fit function, polynomial fit function, index
Fitting function and logistic fit function.
In embodiments of the present invention, obtain and treat fitting data, fitting data is treated using selected at least one fitting function
Be fitted, obtain at least one fitting result, according to the corresponding goodness of fit of each fitting result, to multiple fitting results into
Row screening.Such scheme has evaded a large amount of operations during artificial fitting's data, instead of and is manually chosen over fitting function, manually
Experiment is completed to contrast the complex experiment process of a variety of fitting functions.A variety of data fitting functions are made full use of, data are fitted logical
Cross multithreading and improve efficiency, and the unified goodness of fit for contrasting final multiple fitting functions, obtain more particularly suitable fitting function
And fitting result., data fitting, and most suitable fitting in obtaining to a certain degree are completed so as to complete this adaptivity
Function and the goodness of fit, realize the high efficiency of Function Fitting, and automation, so as to solve data fitting in the prior art
Fitting function is selected to cause the low technical problem of the efficiency of data fitting according to artificial experience.
Brief description of the drawings
Attached drawing described herein is used for providing a further understanding of the present invention, forms the part of the application, this hair
Bright schematic description and description is used to explain the present invention, does not form inappropriate limitation of the present invention.In attached drawing
Fig. 1 is a kind of flow chart of data fitting method according to embodiments of the present invention；
Fig. 2 is a kind of structure diagram of data fitting device according to embodiments of the present invention；
Fig. 3 is a kind of structure diagram of optional data fitting device according to embodiments of the present invention；And
Fig. 4 is a kind of structure diagram of optional data fitting device according to embodiments of the present invention.
Embodiment
In order to make those skilled in the art more fully understand the present invention program, below in conjunction with the embodiment of the present invention
Attached drawing, is clearly and completely described the technical solution in the embodiment of the present invention, it is clear that described embodiment is only
The embodiment of a part of the invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
Member's all other embodiments obtained without making creative work, should all belong to the model that the present invention protects
Enclose.
It should be noted that term " first " in description and claims of this specification and above-mentioned attached drawing, "
Two " etc. be for distinguishing similar object, without for describing specific order or precedence.It should be appreciated that so use
Data can exchange in the appropriate case, so as to the embodiment of the present invention described herein can with except illustrating herein or
Order beyond those of description is implemented.In addition, term " comprising " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, be not necessarily limited to for example, containing the process of series of steps or unit, method, system, product or equipment
Those steps or unit clearly listed, but may include not list clearly or for these processes, method, product
Or the intrinsic other steps of equipment or unit.
In order to make it easy to understand, the professional term occurred in embodiment is explained below：
Data are fitted：Data fitting refers to some discrete function values { f1, f2 ..., fn } of certain known function, by adjusting
Some undetermined coefficient f (λ 1, λ 2 ..., λ n) in the function so that the difference (least square meaning) of the function and known point set is most
It is small.
The goodness of fit：Fitting degree of the regression straight line (curve) to observation.
Multithreading：Refer to the technology for realizing that multiple threads are concurrently performed from software or hardware.With multithreading ability
Computer more than one thread can be performed because have hardware supported in the same time, and then lift disposed of in its entirety performance.
Embodiment 1
According to embodiments of the present invention, there is provided a kind of embodiment of data fitting method is, it is necessary to illustrate, in attached drawing
The step of flow illustrates can perform in the computer system of such as a group of computer-executable instructions, although also,
Logical order is shown in flow chart, but in some cases, can be to perform shown different from order herein or retouch
The step of stating.
Fig. 1 is the flow chart of data fitting method according to embodiments of the present invention, as shown in Figure 1, this method is including as follows
Step：
Fitting data is treated in step S102, acquisition.
Specifically, above-mentioned treat that fitting data can need the data analyzed, such as：For analyzing the number of network behavior
According to, for data for being analyzed the operating parameter of equipment etc..Treat that the quantity step of fitting data is unrestricted, typically have
The data set of multiple data.
It is not high due to easily getting wrong or precision in the data for obtaining data in a kind of optional embodiment
Data, therefore after fitting data is treated in acquisition, treat before fitting data is fitted, can treat fitting data and be sieved
Choosing, to remove the influence that noise is fitted data.
Step S104, treats fitting data using selected at least one fitting function and is fitted, obtain at least one plan
Close result.
Step S106, according to the corresponding goodness of fit of each fitting result, screens multiple fitting results.
The method for the data fitting that above-described embodiment provides treats fitting data by selected at least one fitting function,
And fitting result is most given preferential treatment in selection from multiple fitting results, so as to improve flexibility and the fitting precision of data fitting.
Herein it should be noted that in the prior art the fitting to data do not have a suitable instrument, and above-mentioned reality
Applying the method for example offer can adaptively treat that fitting data selects suitable fitting function from multiple fitting functions, and sieve
Select final fitting result.
From the foregoing, it will be observed that the application above-mentioned steps, which obtain, treats fitting data, plan is treated using selected at least one fitting function
Close data to be fitted, at least one fitting result is obtained, according to the corresponding goodness of fit of each fitting result, to multiple fittings
As a result screened.Such scheme has evaded a large amount of operations during artificial fitting's data, instead of and is manually chosen over fitting letter
Number, manually experiment are completed to contrast the complex experiment process of a variety of fitting functions.A variety of data fitting functions are made full use of, by data
Fitting improves efficiency by multithreading, and the unified goodness of fit for contrasting final multiple fitting functions, obtains more particularly suitable plan
Close function and fitting result.Data fitting is completed so as to complete this adaptivity, and it is most suitable in obtaining to a certain degree
Fitting function and the goodness of fit, realize the high efficiency of Function Fitting, and automation, counted in the prior art so as to solve
According to fitting according to the low technical problem of the efficiency that artificial experience selects fitting function to cause data to be fitted.
Optionally, according to the above embodiments of the present application, using selected at least one fitting function treat fitting data into
Row fitting, obtains at least one fitting result, including：
Step S1041, starts multiple threads and treats fitting data progress by selected at least one fitting function respectively
Fitting, obtains at least one fitting result.
In above-mentioned steps, fitting data will be treated with multiple threads and carries out the fitting of many kinds of function, multithreading here is used
In improving Fitting efficiency, increase is fitted speed.
In a kind of optional embodiment, exemplified by treating fitting data for data acquisition system { a }, { b }, { c }, in selected plan
In the case that conjunction function is respectively A, B, C, D, E, three threads can be started, it is selected using A, B, C, D, E five successively respectively
Fitting function processing is fitted to data acquisition system { a }, { b }, { c }, i.e. first thread uses five functions of A, B, C, D, E
Data acquisition system { a } is handled, the second thread is handled using five function pair data acquisition systems { b } of A, B, C, D, E, and the 3rd
Thread is handled using five function pair data acquisition systems { c } of A, B, C, D, E, obtains multiple fitting results, wherein, each fitting
As a result it is made up of fitting function and corresponding fitting coefficient.
From the foregoing, it will be observed that the process that a variety of fitting functions are not only carried out data fitting by such scheme is unified, it is adaptive
Selection, which is directed to, in a variety of fitting functions treats fitting data, and multithreading is utilized also in fit procedure, fit procedure is added
Speed, improves the efficiency and adaptivity of data fitting, reduces manual operation and intervention, realize the efficient letter of adaptivity
Number fitting.
Optionally, according to the above embodiments of the present application, according to the corresponding goodness of fit of each fitting result, to multiple fittings
As a result screened, including：
Step S1061, calculates the corresponding goodness of fit of each fitting result.
Step S1063, filters out the highest fitting result of the goodness of fit, as final fitting from multiple fitting results
As a result.
In a kind of optional embodiment, fitting data still is treated as exemplified by data acquisition system { a }, { b }, { c } by above-mentioned,
In the case where selected fitting function is respectively A, B, C, D, E, obtain data acquisition system { a } correspond respectively to fitting function A, B,
C, the fitting result of D, E are a1, a2, a3, a4, a5, and data acquisition system { b } corresponds respectively to the fitting of fitting function A, B, C, D, E
As a result it is b1, b2, b3, b4, b5, the fitting result that data acquisition system { c } corresponds respectively to fitting function A, B, C, D, E is c1, c2,
C3, c4, c5, then a1, a2, a3, the corresponding fitting function of maximum in a4, a5 are the fitting function of { a }, b1, b2, b3, b4,
The corresponding fitting function of maximum in b5 is the corresponding fitting function of data acquisition system { b }, c1, c2, c3, c4, the maximum in c5
It is the corresponding fitting function of data acquisition system { c } to be worth corresponding fitting function.
In a kind of optional embodiment, a variety of fitting functions can be collected, will treat that fitting data is carried out with multiple threads
The fitting of many kinds of function, after obtaining each fitting function and treating the fitting result that fitting data is fitted, calculates each intend
Close the corresponding goodness of fit of result.Screened according to the goodness of fit of different functions, take one or several goodness of fit best
Fitting function model, and parameter in fitting function is as final fitting result.
From the foregoing, it will be observed that above-mentioned steps of the present invention calculate the corresponding goodness of fit of each fitting result, from multiple fitting results
In filter out the highest fitting result of the goodness of fit, as final fitting result.Such scheme by the contrast of the goodness of fit,
The corresponding fitting result of most suitable fitting function and fitting function to a certain extent is selected, solves data in the prior art
According to the low technical problem of the efficiency that artificial experience selects fitting function to cause data to be fitted, having reached reduces artificial behaviour for fitting
Make and intervene, realize the effect of the efficient Function Fitting of adaptivity.
Optionally, according to the above embodiments of the present application, in the case where selected fitting function is a fitting function, such as
Fruit treats fitting data with multiple, then starts multiple threads by a selected fitting function while treat fitting data to multiple
It is fitted.
In a kind of optional embodiment, a fitting function is have selected, treats that 5 groups are treated that fitting data is fitted, then are adopted
With the mode for starting multithreading, while treat that fitting data is fitted to five groups, without carrying out data fitting one by one.Such as：
, can in the case where selected fitting function is respectively A, B, C, D, E exemplified by treating fitting data for a data acquisition system { d }
Processing is fitted using five function pair data acquisition systems { d } of A, B, C, D, E respectively to start five threads, obtains each fitting
The corresponding fitting result of function, wherein, each fitting result is made up of fitting function and corresponding fitting coefficient.
Optionally, included according to the above embodiments of the present application, selected at least one fitting function：Linear fit function,
Polynomial fit function, exponential fitting function and logistic fit function.
In the following, a kind of optional embodiment of the data fitting method provided above-described embodiment is described, in the reality
Apply in example, two groups of data are fitted, data character is unknown, and prediction has certain correlation, wants to find a kind of relatively good
Fit approach two groups of data are fitted.
S, read in and treat fitting data.
B, selected a variety of (or a kind of) the fitting function forms of selection.
C, multiple threads are opened, are fitted respectively using the fitting data for the treatment of of every kind of fitting function, digital simulation letter
Several coefficients, and the goodness of fit.
D, more various fitting functions treat the goodness of fit that fitting data is fitted.
E, the highest function of the goodness of fit and relevant parameter are taken as final fitting function result.
Embodiment 2
According to embodiments of the present invention, there is provided a kind of embodiment of data fitting device, Fig. 2 is according to the embodiment of the present application
A kind of data fitting device structure diagram, the example with reference to shown in Fig. 2, which includes：
First acquisition module 20, fitting data is treated for obtaining.
Specifically, above-mentioned treat that fitting data can need the data analyzed, such as：For analyzing the number of network behavior
According to, for data for being analyzed the operating parameter of equipment etc..Treat that the quantity step of fitting data is unrestricted, typically have
The data set of multiple data
Second acquisition module 22, is fitted for treating fitting data using selected at least one fitting function, obtains
To at least one fitting result.
Screening module 24, for according to the corresponding goodness of fit of each fitting result, being screened to multiple fitting results.
The method for the data fitting that above-described embodiment provides treats fitting number by selected one or more fitting functions
According to, and fitting result is most given preferential treatment in selection from multiple fitting results, so as to improve flexibility and the fitting essence of data fitting
Degree.
Herein it should be noted that in the prior art the fitting to data do not have a suitable instrument, and above-mentioned reality
Applying the method for example offer can adaptively treat that fitting data selects suitable fitting function from multiple fitting functions, and sieve
Select final fitting result.
From the foregoing, it will be observed that the application above device, which obtains, treats fitting data, plan is treated using selected at least one fitting function
Close data to be fitted, at least one fitting result is obtained, according to the corresponding goodness of fit of each fitting result, to multiple fittings
As a result screened.Such scheme has evaded a large amount of operations during artificial fitting's data, instead of and is manually chosen over fitting letter
Number, manually experiment are completed to contrast the complex experiment process of a variety of fitting functions.A variety of data fitting functions are made full use of, by data
Fitting improves efficiency by multithreading, and the unified goodness of fit for contrasting final multiple fitting functions, obtains more particularly suitable plan
Close function and fitting result., data fitting is completed so as to complete this adaptivity, and it is most suitable in obtaining to a certain degree
Fitting function and the goodness of fit, realize the high efficiency of Function Fitting, and automation, counted in the prior art so as to solve
According to fitting according to the low technical problem of the efficiency that artificial experience selects fitting function to cause data to be fitted.
Optionally, according to the above embodiments of the present application, with reference to shown in Fig. 3, the second acquisition module 22 includes：
Promoter module 30, fitting number is treated for starting multiple threads by selected at least one fitting function respectively
According to being fitted, at least one fitting result is obtained.
From the foregoing, it will be observed that the process that a variety of fitting functions are not only carried out data fitting by above device is unified, it is adaptive
Selection, which is directed to, in a variety of fitting functions treats fitting data, and multithreading is utilized also in fit procedure, fit procedure is added
Speed, improves the efficiency and adaptivity of data fitting, reduces manual operation and intervention, realize the efficient letter of adaptivity
Number fitting.
Optionally, according to the above embodiments of the present application, with reference to shown in Fig. 4, screening module 24 includes：
Calculating sub module 40, for calculating the corresponding goodness of fit of each fitting result.
Submodule 42 is screened, for filtering out the highest fitting result of the goodness of fit from multiple fitting results, as most
Whole fitting result.
From the foregoing, it will be observed that above device of the present invention calculates the corresponding goodness of fit of each fitting result, from multiple fitting results
In filter out the highest fitting result of the goodness of fit, as final fitting result.Such scheme by the contrast of the goodness of fit,
The corresponding fitting result of most suitable fitting function and fitting function to a certain extent is selected, solves data in the prior art
According to the low technical problem of the efficiency that artificial experience selects fitting function to cause data to be fitted, having reached reduces artificial behaviour for fitting
Make and intervene, realize the effect of the efficient Function Fitting of adaptivity.
Optionally, according to the above embodiments of the present application, in the case where selected fitting function is a fitting function, such as
Fruit treats fitting data with multiple, then starts multiple threads by a selected fitting function while treat fitting data to multiple
It is fitted.
Optionally, included according to the above embodiments of the present application, selected at least one fitting function：Linear fit function,
Polynomial fit function, exponential fitting function and logistic fit function.
The embodiments of the present invention are for illustration only, do not represent the quality of embodiment.
In the above embodiment of the present invention, the description to each embodiment all emphasizes particularly on different fields, and does not have in some embodiment
The part of detailed description, may refer to the associated description of other embodiment.
In several embodiments provided herein, it should be understood that disclosed technology contents, can pass through others
Mode is realized.Wherein, device embodiment described above is only schematical, such as the division of the unit, Ke Yiwei
A kind of division of logic function, can there is an other dividing mode when actually realizing, for example, multiple units or component can combine or
Person is desirably integrated into another system, or some features can be ignored, or does not perform.Another, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be INDIRECT COUPLING or communication link by some interfaces, unit or module
Connect, can be electrical or other forms.
The unit illustrated as separating component may or may not be physically separate, be shown as unit
The component shown may or may not be physical location, you can with positioned at a place, or can also be distributed to multiple
On unit.Some or all of unit therein can be selected to realize the purpose of this embodiment scheme according to the actual needs.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, can also
That unit is individually physically present, can also two or more units integrate in a unit.Above-mentioned integrated list
Member can both be realized in the form of hardware, can also be realized in the form of SFU software functional unit.
If the integrated unit is realized in the form of SFU software functional unit and is used as independent production marketing or use
When, it can be stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially
The part to contribute in other words to the prior art or all or part of the technical solution can be in the form of software products
Embody, which is stored in a storage medium, including some instructions are used so that a computer
Equipment (can be personal computer, server or network equipment etc.) perform each embodiment the method for the present invention whole or
Part steps.And foregoing storage medium includes：USB flash disk, read-only storage (ROM, Read-Only Memory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), mobile hard disk, magnetic disc or CD etc. are various can be with store program codes
Medium.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (10)
- A kind of 1. data fitting method, it is characterised in that including：Fitting data is treated in acquisition；Treat that fitting data is fitted to described using selected at least one fitting function, obtain at least one fitting result；According to the corresponding goodness of fit of each fitting result, multiple fitting results are screened.
- 2. according to the method described in claim 1, it is characterized in that, wait to intend to described using selected at least one fitting function Close data to be fitted, obtain at least one fitting result, including：Start multiple threads and treat that fitting data is fitted to described by selected at least one fitting function respectively, obtain institute State at least one fitting result.
- 3. according to the method described in claim 2, it is characterized in that, according to each corresponding goodness of fit of fitting result, The multiple fitting result is screened, including：Calculate the corresponding goodness of fit of each fitting result；The highest fitting result of the goodness of fit is filtered out from the multiple fitting result, as final fitting result.
- 4. according to the method described in claim 1, it is characterized in that, it is the situation of a fitting function in selected fitting function Under, if treating fitting function with multiple, start multiple threads by selected one fitting function at the same time to multiple Treat that fitting data is fitted.
- 5. according to the method described in claim 1, it is characterized in that, selected at least one fitting function includes：Linearly Fitting function, polynomial fit function, exponential fitting function and logistic fit function.
- 6. a kind of data are fitted device, it is characterised in that including：First acquisition module, fitting data is treated for obtaining；Second acquisition module, for treating that fitting data is fitted to described using selected at least one fitting function, obtains At least one fitting result；Screening module, for according to the corresponding goodness of fit of each fitting result, being screened to multiple fitting results.
- 7. device according to claim 6, it is characterised in that second acquisition module includes：Promoter module, fitting data is treated for starting multiple threads by selected at least one fitting function to described respectively It is fitted, obtains at least one fitting result.
- 8. device according to claim 7, it is characterised in that the screening module includes：Calculating sub module, for calculating the corresponding goodness of fit of each fitting result；Submodule is screened, for filtering out the highest fitting result of the goodness of fit from the multiple fitting result, as final Fitting result.
- 9. device according to claim 6, it is characterised in that the situation in selected fitting function for a fitting function Under, if treating fitting data with multiple, start multiple threads by selected one fitting function at the same time to multiple Treat that fitting data is fitted.
- 10. device according to claim 6, it is characterised in that selected at least one fitting function includes：Linearly Fitting function, polynomial fit function, exponential fitting function and logistic fit function.
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| CN109350098A (en) * | 2018-08-27 | 2019-02-19 | 苏州瑞派宁科技有限公司 | Determination method, reconstruction method and device of signal fitting mode |
| CN109616201A (en) * | 2018-11-09 | 2019-04-12 | 深圳职业技术学院 | A Fatigue Early Warning Method Based on Small Data Dynamic Prediction Model |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108680523A (en) * | 2018-07-10 | 2018-10-19 | 北京北分瑞利分析仪器(集团)有限责任公司 | It is connected the determinand assay method of standard curve using a variety of fit approach |
| CN109350098A (en) * | 2018-08-27 | 2019-02-19 | 苏州瑞派宁科技有限公司 | Determination method, reconstruction method and device of signal fitting mode |
| US11842426B2 (en) | 2018-08-27 | 2023-12-12 | Raycan Technology Co., Ltd. (Suzhou) | Methods for determining a fitting model for a signal, reconstructing a signal and devices thereof |
| CN109616201A (en) * | 2018-11-09 | 2019-04-12 | 深圳职业技术学院 | A Fatigue Early Warning Method Based on Small Data Dynamic Prediction Model |
| CN109616201B (en) * | 2018-11-09 | 2023-10-31 | 深圳职业技术大学 | Fatigue early warning method based on small data dynamic prediction model |
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