Provided is a data processing apparatus creates teacher data used for learning of a machine learning system by classifying data extracted from time series data on the basis of a specific reference. The data processing apparatus includes a data extraction unit which extracts a candidate of teacher data, from time series data, a teacher data creation unit which creates the teacher data based on a label to classify the candidate of teacher data, and the candidate of teacher data which are labeled, and a teacher data complement unit which further extracts the candidate of the teacher data from the time series data that exists between a specific candidate of the teacher data at a specific timing and one of other candidates of the teacher data at a timing different from the specific timing, based on a degree of a variation between these candidates of the teacher data.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A data processing apparatus comprising: a data extraction unit that is configured to extract a candidate of teacher data that is a part of data at a specific timing, from time series data; a teacher data creation unit that is configured to create teacher data on the basis of a label by which the candidate of teacher can be classified and the candidate of teacher data to which the label is assigned; and a teacher data complement unit that is configured to further extract the candidate of the teacher data from the time series data that exists between a specific candidate of the teacher data and one of other candidates of the teacher data on the basis of a degree of a variation between the specific candidate of the teacher data at a specific timing, and the one of other candidates of the teacher data at a timing different from the specific timing, in time series data, the candidate of the teacher data extracted by the teacher data complement unit being assigned with the label that is assigned to either the specific candidate of the teacher data or the one of other candidates of the teacher data and being appended to the teacher data, by the teacher data creation unit, when the degree of the variation is smaller than a first reference. 2. The data processing apparatus according to claim 1, wherein the data extraction unit extracts the candidate of the teacher data from the time series data at a specific time interval that is set to the data processing apparatus. 3. The data processing apparatus according to claim 2, wherein the data extraction unit further extracts a specific number of the candidates of the teacher data, from the time series data which exists between a first candidate of the teacher data and a second candidate of the teacher data, when a variation between the first candidate of the teacher data and the second candidate of the teacher data exceeds a second reference, the first candidate of the teacher data being data at a specific timing in the time series data, and the second candidate of the teacher data being data at a timing different from the specific timing by the predetermined time interval. 4. The data processing apparatus according to claim 1, further comprising: a background image extraction unit that is configured to extract an image whose degree of a variation of a content recorded in time series data in a specific period is smaller than a background image variation reference as an background image, when the time series data is the moving picture data, wherein the data extraction unit determines whether or not to extract the image data as the candidate of the teacher data, on the basis of the degree of the difference between a image data extracted from the moving picture data at a certain timing and the background image. 5. The data processing apparatus according to claim 1, further comprising: a model data storage unit that if configured to store model data that is a result obtained by executing a learning process in a machine learning system by using the teacher data; and a time series data analysis unit that is configured to determine the label assigned to the data included in the time series data by analyzing the time series data by using the model data, and to calculate reliability indicating the degree of certainty with regard to the determination, wherein the teacher data creation unit excludes the candidate of the teacher data, from the creation of the teacher data, when the reliability calculated to the candidate of the teacher data extracted among the time series data is higher than a predetermined reliability reference. 6. The data processing apparatus according to claim 5, further comprising: a teacher data storage unit that is configured to store the teacher data, wherein the time series data analysis unit executes operation for creating the model data by executing the learning process in the machine learning system by using the stored teacher data, and executes operation for storing the created model data in the model data storage unit, when a predetermined amount or more of the teacher data is stored in the teacher data storage unit. 7. The data processing apparatus according to claim 1, wherein the teacher data creation unit displays the candidate of the teacher data to a user, receives the label assigned to the presented candidate of the teacher data by the user, and creates the teacher data on the basis of the received label and the candidate of the teacher data to which the label is to be assigned. 8. The data processing apparatus according to claim 6, wherein the teacher data creation unit displays the candidate of the teacher data to the user, receives the label assigned to the displayed candidate of the teacher data by the user, calculates an accuracy rate of the label assigned to the data extracted as the candidate of the teacher data among the time series data by the time series data analysis unit, on the basis of a result of comparison between the label assigned to the candidate of the teacher data by the time series data analysis unit, and the label assigned to the candidate of the teacher data by the user, and provides user interface to display the calculated accuracy rate. 9. A data processing method comprising: extracting a candidate of teacher data from time series data that exists between a specific candidate of the teacher data and one of other candidates of the teacher data on the basis of a degree of variation between the specific candidate of the teacher data and the one of other candidates of the teacher data, the specific candidate of the teacher data being a part of data at a specific timing in the time series data, and the one of other candidates of the teacher data being a part of data at a timing different from the specific timing in the time series data, assigning a label, by which the candidate of the teacher data can be classified, to the extracted candidate of the teacher data, when the degree of variation is smaller than a first reference, the label assigned to the extracted candidate of the teacher data being the label assigned to either the specific candidate of the teacher data or the one of other candidates of the teacher data, and creating the teacher data on the basis of the data to which the label is assigned. 10. A data processing method comprising: displaying a first candidate of teacher data that is a part of data at a specific timing in time series data, and a second candidate of teacher data that is a part of data at a timing different from the specific timing in the time series data and whose degree of variation from the first candidate of the teacher data exceeds a specific reference, and creating the teacher data on the basis of at least one of the candidates of the teacher data displayed to the user and a label, by which the candidate of the teacher data can be classified, assigned to the candidate of the teacher data by the user. 11. The data processing method according to claim 11, wherein the second candidate of the teacher data is a part of the time series data at a timing different from the specific timing by a predetermined time interval.