A data processing device 100 is intended to provide learning data to a system 200 that generates a prediction model by performing machine learning. The data processing device 100 includes: a data obtaining unit 10 that obtains learning data input from the outside; an encryption unit 20 that encrypts the learning data so that a prediction model generated from the learning data in an unencrypted state and a prediction model generated from the learning data in an encrypted state have a corresponding relationship with each other in terms of parameters, numeric values, and operators; and a data output unit 30 that outputs the encrypted learning data to the system 200.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A data processing device for providing learning data to a system that generates a prediction model by performing machine learning, the data processing device comprising: a data obtaining unit that obtains the learning data input from the outside; an encryption unit that encrypts the learning data so that a prediction model generated from the learning data in an unencrypted state and a prediction model generated from the learning data in an encrypted state have a corresponding relationship with each other in terms of parameters, numeric values, and operators; and a data output unit that outputs the encrypted learning data to the system. 2. The data processing device according to claim 1, wherein the encryption unit comprises an attribute name encryption unit that encrypts attribute names in the learning data, a standardization attribute encryption unit that encrypts data values of the learning data that belong to a specific attribute through standardization processing that uses a specific calculation formula, and a binarization attribute encryption unit that encrypts data values of the learning data that belong to an attribute other than the specific attribute through binarization processing that uses a threshold. 3. The data processing device according to claim 1, wherein when the data obtaining unit has obtained prediction data to be used in prediction based on the prediction model, the encryption unit encrypts the prediction data similarly to the learning data, and the data output unit outputs the encrypted prediction data to the system. 4. The data processing device according to claim 2, further comprising: an attribute name decryption unit that specifies, from the prediction model generated from the encrypted learning data, a portion related to the encrypted attribute names, and decrypts the specified portion; a standardization attribute decryption unit that specifies, from the prediction model, a portion related to values that have undergone the standardization processing, and decrypts the specified portion; and a binarization attribute decryption unit that specifies, from the prediction model, a portion related to values that have undergone the binarization processing, and decrypts the specified portion. 5. A data processing method for providing learning data to a system that generates a prediction model by performing machine learning, the data processing method comprising: (a) a step of obtaining the learning data input from the outside; (b) a step of encrypting the learning data so that a prediction model generated from the learning data in an unencrypted state and a prediction model generated from the learning data in an encrypted state have a corresponding relationship with each other in terms of parameters, numeric values, and operators; and (c) a step of outputting the encrypted learning data to the system. 6. A non-transitory computer-readable recording medium having recorded therein a program for, using a computer, providing learning data to a system that generates a prediction model by performing machine learning, the program including an instruction that causes the computer to execute: (a) a step of obtaining the learning data input from the outside; (b) a step of encrypting the learning data so that a prediction model generated from the learning data in an unencrypted state and a prediction model generated from the learning data in an encrypted state have a corresponding relationship with each other in terms of parameters, numeric values, and operators; and (c) a step of outputting the encrypted learning data to the system.