CN109726198A - Method for processing abnormal data and device - Google Patents
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- CN109726198A CN109726198A CN201811487108.2A CN201811487108A CN109726198A CN 109726198 A CN109726198 A CN 109726198A CN 201811487108 A CN201811487108 A CN 201811487108A CN 109726198 A CN109726198 A CN 109726198A
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Abstract
The present invention provides a kind of method for processing abnormal data and device, this method is applied to technical field of data processing, which comprises obtains pending data；Rejecting outliers method is determined according to the distribution of the pending data；The exceptional value in the pending data is detected according to the rejecting outliers method；The exceptional value is modified according to default modification method.Method for processing abnormal data and device provided by the invention can be detected quickly and correct exceptional value.
Description
Technical field
The invention belongs to technical field of data processing, are to be related to a kind of method for processing abnormal data and dress more specifically
It sets.
Background technique
In reality, since mistake or natural mistake will lead to generation data outliers, in the environment of multi-data source
Under, there is data exception and generate the probability of data collision greatly increasing.How to handle these exceptional values is data cleansing institute
The important topic faced.
In data handling, especially when making Function Fitting, the appearance of abnormal point not only can significantly change function
The effect of fitting, and the gradient of function can also be made unusual gradient occur sometimes, it is easy to lead to the termination of algorithm, thus shadow
Ring the functional relation between research variable.In order to effectively avoid loss caused by these abnormal points, it would be desirable to take certain
Method it is handled.But in the case where multi-data source, big data quantity, lack a kind of detection exceptional value in the prior art
And to the method that exceptional value is quickly handled.
Summary of the invention
The purpose of the present invention is to provide a kind of method for processing abnormal data and devices, existing in the prior art to solve
The technical issues of dealing of abnormal data can not quickly be carried out.
The embodiment of the present invention in a first aspect, providing a kind of method for processing abnormal data, which comprises
Obtain pending data；
Rejecting outliers method is determined according to the distribution of the pending data；
The exceptional value in the pending data is detected according to the rejecting outliers method；
The exceptional value is modified according to default modification method.
The second aspect of the embodiment of the present invention, provides a kind of dealing of abnormal data device, and described device includes:
Data acquisition module, for obtaining pending data；
Judgment module, for determining rejecting outliers method according to the distribution of the pending data；
Detection module, for detecting the exceptional value in the pending data according to the rejecting outliers method；
Correction module, for being modified according to default modification method to the exceptional value.
The third aspect of the embodiment of the present invention, provides a kind of terminal device, including memory, processor and is stored in
In the memory and the computer program that can run on the processor, when the processor executes the computer program
The step of realizing above-mentioned method for processing abnormal data.
The fourth aspect of the embodiment of the present invention, provides a kind of computer readable storage medium, described computer-readable to deposit
Storage media is stored with computer program, and the computer program realizes above-mentioned method for processing abnormal data when being executed by processor
The step of.
The beneficial effect of method for processing abnormal data and device provided by the invention is: abnormal data provided by the invention
Processing method and processing device is provided with different pending data rejecting outliers method and different according to different data distribution states
Constant value modification method realizes that simply data calculation time is at low cost, can be realized the quick detection and amendment of abnormal data.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without creative efforts, can also be attached according to these
Figure obtains other attached drawings.
Fig. 1 is the flow diagram for the method for processing abnormal data that one embodiment of the invention provides；
Fig. 2 be another embodiment of the present invention provides method for processing abnormal data flow diagram；
Fig. 3 is the flow diagram for the method for processing abnormal data that yet another embodiment of the invention provides；
Fig. 4 is the flow diagram for the method for processing abnormal data that further embodiment of this invention provides；
Fig. 5 is the flow diagram for the method for processing abnormal data that further embodiment of this invention provides；
Fig. 6 is the structural block diagram for the dealing of abnormal data device that one embodiment of the invention provides；
Fig. 7 is the schematic block diagram for the terminal device that one embodiment of the invention provides.
Specific embodiment
In order to which technical problems, technical solutions and advantages to be solved are more clearly understood, tie below
Accompanying drawings and embodiments are closed, the present invention will be described in further detail.It should be appreciated that specific embodiment described herein is only
To explain the present invention, it is not intended to limit the present invention.
Referring to FIG. 1, the flow diagram of the method for processing abnormal data provided for one embodiment of the invention.This method packet
It includes:
S101: pending data is obtained.
In the present embodiment, settable timing acquisition task carries out pending data in batches, timing acquisition task to be arranged
Batch cycle obtains pending data.
S102: rejecting outliers method is determined according to the distribution of pending data.
In the present embodiment, the distribution of pending data includes normal distribution and Non-Gaussian Distribution, if number to be processed
According to all normal distribution is met, then the exceptional value in pending data is determined using normal distribution method for detecting abnormality.If wait locate
Make the data set meet normal distribution there is no a certain data set in reason data, then uses Non-Gaussian Distribution method for detecting abnormality
Determine the exceptional value of pending data.If there are partial data collection to meet normal distribution in pending data, meet normal state point
The data set of cloth uses normal distribution method for detecting abnormality, and the data set for not meeting normal distribution is examined extremely using Non-Gaussian Distribution
Survey method.
S103: the exceptional value in pending data is detected according to rejecting outliers method.
In the present embodiment, normal distribution method for detecting abnormality the average and standard deviation of data set can detect according to
Exceptional value, Non-Gaussian Distribution method for detecting abnormality can detect exceptional value according to box-shaped figure.
S104: exceptional value is modified according to default modification method.
In the present embodiment, corresponding to the distribution of pending data, the present embodiment can be used two kinds of modification methods into
The amendment of row exceptional value.Two of them detection method are as follows: normal distribution modification method and Non-Gaussian Distribution modification method.
As can be seen from the above description, method for processing abnormal data provided in an embodiment of the present invention is according to different data distribution shapes
State is provided with different pending data rejecting outliers methods and abnormal value correction method, realizes simple, data calculation time
It is at low cost, it can be realized the quick detection and amendment of abnormal data.
Please also refer to Fig. 1 and Fig. 2, Fig. 2 is the process for the method for processing abnormal data that another embodiment of the application provides
Schematic diagram.On the basis of the above embodiments, step S102 can be described in detail are as follows:
S201: it if pending data is normal distribution, is carried out according to the average and standard deviation of pending data abnormal
Value detection.
In the present embodiment, normal distribution detection method are as follows: according to the average and standard deviation of pending data obtain to
The deviation value for handling data point in data, can determine whether the data point is different according to the departure degree of a certain data point deviation value
Constant value.
S202: if pending data is Non-Gaussian Distribution, rejecting outliers are carried out according to box-shaped figure.
In the present embodiment, Non-Gaussian Distribution detection method are as follows: according to the truncation range of box-shaped figure to pending data
Data point is detected, if a certain data point is except the truncation range of box-shaped figure in pending data, it is determined that the data point
For exceptional value.
A kind of specific reality please also refer to Fig. 1 and Fig. 2, as method for processing abnormal data provided in an embodiment of the present invention
Apply mode.On the basis of the above embodiments, step S102 can also include:
S203: the distribution of pending data is determined according to K-S method of inspection.
In the present embodiment, normal data can be first obtained, then calculates separately accumulative point of pending data and normal data
Cloth function calculates the maximum value of the two Cumulative Distribution Function difference, if the maximum value is in default confidence interval, it is determined that wait locate
Reason data are normal distribution, if the maximum value is not in default confidence interval, it is determined that pending data is Non-Gaussian Distribution.
Please also refer to Fig. 1 and Fig. 3, Fig. 3 is the process for the method for processing abnormal data that yet another embodiment of the invention provides
Schematic diagram, on the basis of the above embodiments, carrying out rejecting outliers according to the average and standard deviation of pending data can be with
Include:
S301: the average and standard deviation of pending data is calculated.
S302: if the difference of a certain data point and average value in pending data is greater than 3 times of standard deviation, it is determined that should
Data point is exceptional value.
In the present embodiment, exceptional value can be detected according to the average and standard deviation of pending data, it can also be according to following
Method detects exceptional value:
Pending data is grouped first, every 100 data are one group.Being averaged for every set of group data is calculated again
Value and standard deviation calculate the deviation value of each data point and the difference of average value as each data point in packet data, if certain
The deviation value of one data point and the ratio of standard deviation are greater than critical value, it is determined that the data point is exceptional value.Wherein, critical value can
Determine that pendulous frequency is 100 herein with pendulous frequency lookup Grubbs table according to preset detection is horizontal.
Please also refer to Fig. 1 and Fig. 4, Fig. 4 is the process for the method for processing abnormal data that the another embodiment of the application provides
Schematic diagram.On the basis of the above embodiments, carrying out rejecting outliers according to box-shaped figure may include:
S401: box-shaped figure is established according to pending data.
In the present embodiment, the upper quartile of box-shaped figure, lower quartile and four points can be determined according to pending data
Digit spacing determines the truncation range of box-shaped figure further according to upper quartile, lower quartile and interquartile range.For example,
If upper quartile is QU, lower quartile QL, interquartile range IQR, then it is [QL-1.5IQR, QU+ that range, which is truncated,
1.5IQR]。
S402: if a certain data point is not within the scope of the truncation of box-shaped figure in pending data, it is determined that the data point
For exceptional value.
In the present embodiment, if a certain data point is not within the scope of box-shaped figure is truncated in pending data, i.e. the data
The data value of point is less than QL-1.5IQR or is greater than QU+1.5IQR, it is determined that the data point is exceptional value.
Please also refer to Fig. 1 to Fig. 5, Fig. 5 is the process for the method for processing abnormal data that the another embodiment of the application provides
Schematic diagram.On the basis of the above embodiments, above-mentioned steps S104 can be described in detail are as follows:
S501: if the data set where a certain exceptional value is normal distribution, the exceptional value is deleted from data set.
In the present embodiment, normal distribution modification method may be:
If the data set where a certain exceptional value is normal distribution, according to the type of the exceptional value, with the type data
Average value or median replace the exceptional value.
S502: if data set where a certain exceptional value is Non-Gaussian Distribution, according to interpolating function to the exceptional value into
Row amendment.
In the present embodiment, Non-Gaussian Distribution modification method may be:
It, can be according to known in data set where the exceptional value if the data set where a certain exceptional value is Non-Gaussian Distribution
Normal data points establish suitable interpolating function, and the replacement values of the exceptional value are determined further according to the interpolating function, use the replacement
Value replaces the exceptional value.
Corresponding to the method for processing abnormal data of foregoing embodiments, Fig. 6 is the abnormal data that one embodiment of the invention provides
The structural block diagram of processing unit.For ease of description, only parts related to embodiments of the present invention are shown.With reference to Fig. 6, the dress
Set includes: data acquisition module 10, judgment module 20, detection module 30 and correction module 40.
Wherein, data acquisition module 10, for obtaining pending data.
Judgment module 20 determines rejecting outliers method for the distribution according to pending data.
Detection module 30, for detecting the exceptional value in pending data according to rejecting outliers method.
Correction module 40, for being modified according to default modification method to exceptional value.
With reference to Fig. 6, judgment module 20 may include: in another embodiment of the present invention
First judging unit 21, if being normal distribution for pending data, according to the average value of pending data and
Standard deviation carries out rejecting outliers.
Second judgment unit 22 carries out exceptional value inspection according to box-shaped figure if being Non-Gaussian Distribution for pending data
It surveys.
With reference to Fig. 6, in yet another embodiment of the present invention, judgment module 20 can also include:
Status determining unit 23, for determining the distribution of pending data according to K-S method of inspection.
With reference to Fig. 6, in yet another embodiment of the present invention, detection module 30 may include:
Computing unit 31, for calculating the average and standard deviation of pending data.
First detection unit 32, if the difference for a certain data point and average value in pending data is greater than standard deviation
3 times, it is determined that the data point be exceptional value.
With reference to Fig. 6, in yet another embodiment of the present invention, detection module 30 can also include:
Unit 33 is established, for establishing box-shaped figure according to pending data.
Second detection unit 34, if for data point a certain in pending data not within the scope of the truncation of box-shaped figure,
Then determine that the data point is exceptional value.
With reference to Fig. 6, in yet another embodiment of the present invention, correction module 40 includes:
First amending unit 41 is deleted from data set if being normal distribution for the data set where a certain exceptional value
Except the exceptional value.
Second amending unit 42, if being Non-Gaussian Distribution for the data set where a certain exceptional value, according to interpolation letter
It is several that the exceptional value is modified.
Referring to Fig. 7, Fig. 7 is a kind of schematic block diagram for terminal device that one embodiment of the invention provides.Sheet as shown in Figure 7
Terminal 600 in embodiment may include: one or more processors 601, one or more input equipments 602, one or more
A output equipment 603 and one or more memories 604.Above-mentioned processor 601, input equipment 602, then output equipment 603 and
Memory 604 completes mutual communication by communication bus 605.Memory 604 is for storing computer program, computer journey
Sequence includes program instruction.Processor 601 is used to execute the program instruction of the storage of memory 604.Wherein, processor 601 is configured
For operating the function of each module/unit in above-mentioned each Installation practice, such as mould shown in Fig. 6 below caller instruction execution
The function of block 10 to 40.
It should be appreciated that in embodiments of the present invention, alleged processor 601 can be central processing unit (Central
Processing Unit, CPU), which can also be other general processors, digital signal processor (Digital
Signal Processor, DSP), specific integrated circuit (Application Specific Integrated Circuit,
ASIC), ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic
Device, discrete gate or transistor logic, discrete hardware components etc..General processor can be microprocessor or this at
Reason device is also possible to any conventional processor etc..
Input equipment 602 may include that Trackpad, fingerprint adopt sensor (for acquiring the finger print information and fingerprint of user
Directional information), microphone etc., output equipment 603 may include display (LCD etc.), loudspeaker etc..
The memory 604 may include read-only memory and random access memory, and to processor 601 provide instruction and
Data.The a part of of memory 604 can also include nonvolatile RAM.For example, memory 604 can also be deposited
Store up the information of device type.
In the specific implementation, processor 601 described in the embodiment of the present invention, input equipment 602, output equipment 603 can
Execute realization described in the first embodiment and second embodiment of method for processing abnormal data provided in an embodiment of the present invention
The implementation of terminal described in the embodiment of the present invention also can be performed in mode, and details are not described herein.
A kind of computer readable storage medium is provided in another embodiment of the invention, and computer readable storage medium is deposited
Computer program is contained, computer program includes program instruction, and above-described embodiment side is realized when program instruction is executed by processor
All or part of the process in method can also instruct relevant hardware to complete by computer program, and computer program can
It is stored in a computer readable storage medium, the computer program is when being executed by processor, it can be achieved that above-mentioned each method
The step of embodiment.Wherein, computer program includes computer program code, and computer program code can be source code shape
Formula, object identification code form, executable file or certain intermediate forms etc..Computer-readable medium may include: that can carry meter
Any entity or device of calculation machine program code, recording medium, USB flash disk, mobile hard disk, magnetic disk, CD, computer storage, only
Read memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electricity load
Wave signal, telecommunication signal and software distribution medium etc..It should be noted that the content that computer-readable medium includes can root
Increase and decrease appropriate is carried out according to the requirement made laws in jurisdiction with patent practice, such as in certain jurisdictions, according to vertical
Method and patent practice, computer-readable medium do not include be electric carrier signal and telecommunication signal.
Computer readable storage medium can be the internal storage unit of the terminal of aforementioned any embodiment, such as terminal
Hard disk or memory.Computer readable storage medium is also possible to the External memory equipment of terminal, such as the grafting being equipped in terminal
Formula hard disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card, flash card
(Flash Card) etc..Further, computer readable storage medium can also both include the internal storage unit of terminal or wrap
Include External memory equipment.Computer readable storage medium is for storing other program sum numbers needed for computer program and terminal
According to.Computer readable storage medium can be also used for temporarily storing the data that has exported or will export.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps, can be realized with electronic hardware, computer software, or a combination of the two, in order to clearly demonstrate hardware
With the interchangeability of software, each exemplary composition and step are generally described according to function in the above description.This
A little functions are implemented in hardware or software actually, the specific application and design constraint depending on technical solution.Specially
Industry technical staff can use different methods to achieve the described function each specific application, but this realization is not
It is considered as beyond the scope of this invention.
It is apparent to those skilled in the art that for convenience of description and succinctly, the end of foregoing description
The specific work process at end and unit, can refer to corresponding processes in the foregoing method embodiment, details are not described herein.
In several embodiments provided herein, it should be understood that disclosed terminal and method can pass through it
Its mode is realized.For example, the apparatus embodiments described above are merely exemplary, for example, the division of unit, only
A kind of logical function partition, there may be another division manner in actual implementation, for example, multiple units or components can combine or
Person is desirably integrated into another system, or some features can be ignored or not executed.In addition, it is shown or discussed it is mutual it
Between coupling, direct-coupling or communication connection can be through some interfaces, the INDIRECT COUPLING or communication link of device or unit
It connects, is also possible to electricity, mechanical or other form connections.
Unit may or may not be physically separated as illustrated by the separation member, shown as a unit
Component may or may not be physical unit, it can and it is in one place, or may be distributed over multiple networks
On unit.It can select some or all of unit therein according to the actual needs to realize the mesh of the embodiment of the present invention
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, is also possible to two or more units and is integrated in one unit.It is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.
More than, only a specific embodiment of the invention, but scope of protection of the present invention is not limited thereto, and it is any to be familiar with
Those skilled in the art in the technical scope disclosed by the present invention, can readily occur in various equivalent modifications or substitutions,
These modifications or substitutions should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be wanted with right
Subject to the protection scope asked.
Claims (10)
1. a kind of method for processing abnormal data characterized by comprising
Obtain pending data；
Rejecting outliers method is determined according to the distribution of the pending data；
The exceptional value in the pending data is detected according to the rejecting outliers method；
The exceptional value is modified according to default modification method.
2. method for processing abnormal data as described in claim 1, which is characterized in that point according to the pending data
Cloth state determines rejecting outliers method, comprising:
If the pending data is normal distribution, exceptional value is carried out according to the average and standard deviation of the pending data
Detection；
If the pending data is Non-Gaussian Distribution, rejecting outliers are carried out according to box-shaped figure.
3. method for processing abnormal data as claimed in claim 2, which is characterized in that point according to the pending data
Cloth state determines rejecting outliers method further include:
The distribution of the pending data is determined according to K-S method of inspection.
4. method for processing abnormal data as claimed in claim 2, which is characterized in that described according to the flat of the pending data
Mean value and standard deviation carry out rejecting outliers
Calculate the average and standard deviation of the pending data；
If the difference of a certain data point and the average value in the pending data is greater than 3 times of the standard deviation, really
The fixed data point is exceptional value.
5. method for processing abnormal data as claimed in claim 4, which is characterized in that described to carry out exceptional value inspection according to box-shaped figure
Survey includes:
Box-shaped figure is established according to the pending data；
If a certain data point is not within the scope of the truncation of the box-shaped figure in the pending data, it is determined that the data point is
Exceptional value.
6. method for processing abnormal data as described in claim 1, which is characterized in that the basis presets modification method to described
Exceptional value, which is modified, includes:
If the data set where a certain exceptional value is normal distribution, the exceptional value is deleted from the data set；
If the data set where a certain exceptional value is Non-Gaussian Distribution, the exceptional value is modified according to interpolating function.
7. a kind of dealing of abnormal data device characterized by comprising
Data acquisition module, for obtaining pending data；
Judgment module, for determining rejecting outliers method according to the distribution of the pending data；
Detection module, for detecting the exceptional value in the pending data according to the rejecting outliers method；
Correction module, for being modified according to default modification method to the exceptional value.
8. dealing of abnormal data device as claimed in claim 7, which is characterized in that the judgment module includes:
First judging unit, if being normal distribution for the pending data, according to the average value of the pending data
Rejecting outliers are carried out with standard deviation；
Second judgment unit carries out rejecting outliers according to box-shaped figure if being Non-Gaussian Distribution for the pending data.
9. a kind of terminal device, including memory, processor and storage are in the memory and can be on the processor
The computer program of operation, which is characterized in that the processor realizes such as claim 1 to 6 when executing the computer program
The step of any one the method.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In when the computer program is executed by processor the step of any one of such as claim 1 to 6 of realization the method.
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| CN112861947B (en) * | 2021-01-29 | 2024-04-19 | 中铁第一勘察设计院集团有限公司 | Sensor data processing method and device and computing equipment |
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