DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1 – 7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
As to claims 1,
Step 2A, Prong One
The claim recites in part:
one or more second setting values that respectively indicate differences with respect to the first setting value
As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, generating hyperparameter groups is a fundamental element of thinking, where the human brain abstracts properties and functions based on similarities to form concepts or groups
Accordingly, at Step 2A, Prong One, the claim is directed to an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of:
accepting one or more of the second setting values in each of two or more of the groups;
which amounts to extra-solution activity of gathering data for use in the claimed process. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity to a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
The claim further recites:
regarding the second setting values, a plurality of groups of differences of different portions in the first setting value are set
which is recited at a high-level of generality with no detail of the process to set the values in the machine learning model and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
The non-transitory computer-readable recording medium is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
In addition, the recitation of setting value, hyperparameters, machine learning model, and hyperparameter groups amounts amounts to generally linking the use of the judicial exception to a particular environment of field of use (See MPEP 2106.05(h)). As such, the claim does not integrate the judicial exception into a practical application.
Accordingly, at Step 2A, Prong Two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
accepting one or more of the second setting values in each of two or more of the groups;
are recited at a high level of generality and amounts to extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
The claim further recites:
regarding the second setting values, a plurality of groups of differences of different portions in the first setting value are set
which is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
The non-transitory computer-readable recording medium is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
The recitation of setting value, hyperparameters, machine learning model, and hyperparameter groups amounts to generally linking the use of the judicial exception to a particular environment of field of use (See MPEP 2106.05(h)).
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
As to claim 2,
Step 2A, Prong One
The claim recites in part:
generating the plurality of hyperparameter groups by adding the differences indicated by the respective second setting values to the first setting value
As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, generating hyperparameter groups is a fundamental element of thinking, where the human brain abstracts properties and functions based on similarities to form concepts or groups
Accordingly, at Step 2A, Prong One, the claim is directed to an abstract idea.
Step 2A, Prong Two
Further the claim does not include additional elements that integrate this abstract idea into a practical application. “Generating” is performed using generic computer components performing their typical functions and does not provide a meaningful technological improvement.
Accordingly, at Step 2A, Prong Two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B
Nothing in the claim adds “significantly more” beyond generic computing.
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
As to claims 3,
Step 2A, Prong One
The claim recites in part:
generating the plurality of hyperparameter groups by adding the differences indicated by the second setting values to the first setting value individually on a group-by-group basis
As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, generating hyperparameter groups is a fundamental element of thinking, where the human brain abstracts properties and functions based on similarities to form concepts or groups
Accordingly, at Step 2A, Prong One, the claim is directed to an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of:
accepting one or more of the second setting values in each of two or more of the groups;
which amounts to extra-solution activity of gathering data for use in the claimed process. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity to a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
The claim further recites:
regarding the second setting values, a plurality of groups of differences of different portions in the first setting value are set, and wherein
which is recited at a high-level of generality with no detail of the process to set the values in the machine learning model and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, Prong Two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
accepting one or more of the second setting values in each of two or more of the groups;
are recited at a high level of generality and amounts to extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
The claim further recites:
regarding the second setting values, a plurality of groups of differences of different portions in the first setting value are set, and wherein
which is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
As to claims 4,
Step 2A, Prong One
The claim does not recite an abstract idea or any other judicial exception and therefore passes Step 2A, Prong of the Alice/Mayo analysis.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of:
storing, in a case where a machine learning process is tried by using the hyperparameter groups set in the machine learning model, in a storage device tried hyperparameter groups that have been used in a trial;
upon reception of designation of the tried hyperparameter groups, obtaining the tried hyperparameter groups from the storage device and causing the obtained tried hyperparameter groups to be set in the machine learning model.
which amounts to extra-solution activity of gathering data for use in the claimed process. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity to a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
The claim further recites:
causing the obtained tried hyperparameter groups to be set in the machine learning model.
which is recited at a high-level of generality with no detail of the process to set the values in the machine learning model and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
The claim further recites a storage device which is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2A, Prong Two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
storing, in a case where a machine learning process is tried by using the hyperparameter groups set in the machine learning model, in a storage device tried hyperparameter groups that have been used in a trial;
upon reception of designation of the tried hyperparameter groups, obtaining the tried hyperparameter groups from the storage device and causing the obtained tried hyperparameter groups to be set in the machine learning model.
are recited at a high level of generality and amounts to extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
The claim further recites:
causing the obtained tried hyperparameter groups to be set in the machine learning model.
which is recited at a high-level of generality with no detail of the training process and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
The storage device amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
As to claims 5,
Step 2A, Prong One
The claim does not recite an abstract idea or any other judicial exception and therefore passes Step 2A, Prong of the Alice/Mayo analysis.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of:
storing, in a case where a machine learning process is tried by using the hyperparameter groups set in the machine learning model, in a storage device tried hyperparameter information in which information on the first setting value used to generate tried hyperparameter groups used in a trial and the second setting values used to generate the tried hyperparameter groups used in the trial is registered
which amounts to extra-solution activity of gathering data for use in the claimed process. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity to a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
The claim further recites:
upon reception of a request for displaying of the tried hyperparameter information, obtaining the tried hyperparameter information from the storage device and causing the tried hyperparameter information to be displayed in a display device
these elements are recited at a high-level of generality and amounts to no more than adding the words “apply it” to the judicial exception. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f)). These limitations also amount to extra solution activity because it is a mere nominal or tangential addition to the claim, amounting to mere data output (see MPEP 2106.05(g)).
The claim further recites a storage device and a display device which are recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2A, Prong Two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
storing, in a case where a machine learning process is tried by using the hyperparameter groups set in the machine learning model, in a storage device tried hyperparameter information in which information on the first setting value used to generate tried hyperparameter groups used in a trial and the second setting values used to generate the tried hyperparameter groups used in the trial is registered
are recited at a high level of generality and amounts to extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. The limitations:
upon reception of a request for displaying of the tried hyperparameter information, obtaining the tried hyperparameter information from the storage device and causing the tried hyperparameter information to be displayed in a display device
are recited at a high-level of generality and amounts to no more than adding the words “apply it” to the judicial exception. These limitations also amount to extra solution activity because it is a mere nominal or tangential addition to the claim, amounting to mere data output (see MPEP 2106.05(g)). The courts have similarly found limitations directed to displaying a result, recited at a high level of generality, to be well-understood, routine, and conventional. See (MPEP 2106.05(d)(II), "presenting offers and gathering statistics.", “determining an estimated outcome and setting a price”).
The storage device and display device are recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Claim 6 has similar limitations as claim 1. Therefore, the claim is rejected for the same reasons as above.
Claim 7 has similar limitations as claim 1. Therefore, the claim is rejected for the same reasons as above.
The claim further recites an information processing apparatus, a memory, and a processor which are recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 4, 6, and 7 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Gunes et al (US 2019/0370684).
As to claim 1, Gunes et al teaches a non-transitory computer-readable recording medium storing a setting program for causing a computer to execute a process (paragraph [0003]….a non-transitory computer-readable medium is provided having stored thereon computer-readable instructions that, when executed by a computing device) comprising:
accepting designation of a first setting value for an entirety of a plurality of hyperparameters (paragraph [0092]…in operation 218, a hyperparameter configuration is randomly selected for each training model iteration from the list of hyperparameter configurations) included in a machine learning model (paragraph [0012]…machine learning model) and designation of one or more second setting values (paragraph [0096]… operation 224, the feature set and hyperparameter configuration pair for the current iteration are selected) that respectively indicate differences (paragraph [0092]…each iteration of the number of training model iterations has a selected feature set and a selected hyperparameter configuration. A test may confirm that each feature set and hyperparameter configuration pair is unique ; Examiner’s Note: Each configuration pair is unique so the there are differences between the configurations) with respect to the first setting value; and
causing a plurality of hyperparameter groups (paragraph [0097]… In an operation 226, a model of the model type indicated in operation 208 is trained using each observation vector read from training dataset 124 with the features (variables) defined by the feature set and using the hyperparameter values defined by the hyperparameter configuration) generated based on the first setting value that has been designated and the second setting values that have been designated to be set in the machine learning model (paragraph [0090]… the array or a list of hyperparameter configurations may be created for each unique combination of hyperparameter values, for example, using the lower bound value, the upper bound value, and the iteration value and/or the list of values defined for each hyperparameter based on the model type selected in operation 208).
As to claim 4, Gunes et al teaches a non-transitory computer-readable recording medium, the process further comprising:
storing (paragraph [0108]… 108 is an electronic holding place or storage), in a case where a machine learning process is tried by using the hyperparameter groups set in the machine learning model, in a storage device tried hyperparameter groups that have been used in a trial (paragraph [0085]…Feature sets A and B would have a similar test error for a hyperparameter configuration if they both include and exclude some essential information. This property of factorization machine models is useful for learning more about the true features behind the input dataset); and,
upon reception of designation of the tried hyperparameter groups, obtaining the tried hyperparameter groups from the storage device and causing the obtained tried hyperparameter groups to be set in the machine learning model (paragraph [0103]… an estimation model of the estimation model type indicated in operation 210 is trained using the feature set index, hyperparameter configuration index, and accuracy value or prediction error as inputs as well as any hyperparameter(s) defined for the estimation model type indicated in operation 210. In an alternative embodiment, when the iteration counter is stored, the iteration counter may be used to determine the feature set index and the hyperparameter configuration index).
Claim 6 has similar limitations as claim 1. Therefore, the claim is rejected for the same reasons as above.
Claim 7 has similar limitations as claim 1. Therefore, the claim is rejected for the same reasons as above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gunes et al (US 2019/0370684) in view of Chen et al (US 10,832,174)
As to claim 2, Gunes et al teaches a plurality of hyperparameter groups (paragraph [0097]… In an operation 226, a model of the model type indicated in operation 208 is trained using each observation vector read from training dataset 124 with the features (variables) defined by the feature set and using the hyperparameter values defined by the hyperparameter configuration).
Gunes et al fails to explicitly show/teach generating the plurality of hyperparameter groups by adding the differences indicated by the respective second setting values to the first setting value.
However, Chen et al teaches generating the plurality of hyperparameter groups by adding the differences indicated by the respective second setting values to the first setting value (column 19, lines 60 – 67… a convergence criterion may be that a total sum of a difference between the hyperparameters selected in two adjacent iterations is smaller than search convergence value c.sub.s.).
Therefore, it would have been obvious for one having ordinary skill in the art, at the time the invention was made for Gunes et al to generate the plurality of hyperparameter groups by adding the differences indicated by the respective second setting values to the first setting value, as in Chen et al, for the purpose of providing a machine learning model with a good set of features from which to train. Better features provide flexibility, simpler models, and improved prediction accuracy.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gunes et al (US 2019/0370684) in view of Morgan et al (US 2021/0073592)
As to claim 5, Gunes et al teaches the non-transitory computer-readable recording medium further comprising:
storing, in a case where a machine learning process is tried by using the hyperparameter groups set in the machine learning model (paragraph [0030]… the data from these things collected and processed within the things and/or external to the things before being stored in the input dataset that is split or partitioned into training dataset 124 and validation dataset 126), in a storage device tried hyperparameter information in which information on the first setting value (paragraph [0096]… operation 224, the feature set and hyperparameter configuration pair for the current iteration are selected) used to generate tried hyperparameter groups used in a trial and the second setting values used to generate the tried hyperparameter groups used in the trial is registered (paragraph [0026]… a cross validation option may be selected by a user or other technique for determining training dataset 124 and validation dataset 126 from the input dataset. Training dataset 124 and validation dataset 126 each may include, for example, a plurality of rows and a plurality of columns. The plurality of rows may be referred to as observation vectors or records (observations), and the columns may be referred to as variables or features. Training dataset 124 and validation dataset 126 may be transposed. The plurality of variables v.sub.i may define multiple dimensions).
Gunes et al fails to explicitly show/teach upon reception of a request for displaying of the tried hyperparameter information, obtaining the tried hyperparameter information from the storage device and causing the tried hyperparameter information to be displayed in a display device.
However, Morgan et al teaches upon reception of a request for displaying of the tried hyperparameter information, obtaining the tried hyperparameter information from the storage device and causing the tried hyperparameter information to be displayed in a display device (paragraph [0430]… [0430] The user may be able to specify the response type (e.g., a threshold or match target type). For instance, a validation specification may comprise a request to identify a set of inputs that will exceed a threshold for a response of the system of operation according to a test case of a test suite. In FIG. 50B, a test suite 5050 shows test cases for recording responses according to each of the criteria shown in graphical user interface 5000 (e.g., if the threshold is passed or a target is reached). The responses may be specified by the user (e.g., to record pass or fail for displaying to a user). In this example a covering array of strength 2 is selected for a subset of the hyperparameters not involved in advanced options shown in FIG. 42)
Therefore, it would have been obvious for one having ordinary skill in the art, at the time the invention was made for Gunes et al’s upon reception of a request for displaying of the tried hyperparameter information, obtaining the tried hyperparameter information from the storage device and causing the tried hyperparameter information to be displayed in a display device, as in Morgan et al, for the purpose of providing observations how design options for the design space would influence the experiments.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRANDON S COLE whose telephone number is (571)270-5075. The examiner can normally be reached Mon - Fri 7:30pm - 5pm EST (Alternate Friday's Off).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Omar Fernandez can be reached at 571-272-2589. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BRANDON S COLE/ Primary Examiner, Art Unit 2128