CTFR 17/465,018 CTFR 99378 Detailed Action This action is in response to the amendment filed on 02/04/2026 for application 17/465,018, in which: Claims 1 , 8 , and 15 are independent claims. Claims 1 , 3 , 5 , 8 , 10 , 12 , 15 , and 17 - 18 are currently amended. Claims 4 , 6 - 7 , 11 , 13 - 14 , and 19 - 20 are canceled. Claims 21 - 28 are newly added. Claims 1 - 3 , 5 , 8 - 10 , 12 , 15 - 18 , and 21 - 28 are currently pending. Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Regarding the 35 U.S.C. § 103 Rejections: Applicant's amendments to the independent Claims overcome the previous 35 U.S.C. 103 rejections. More information below within the Examiner Comments section. Response to Arguments 07-37 AIA Applicant's arguments filed 02/04/2026 have been fully considered but they are not persuasive. Regarding the 35 U.S.C. § 101 Rejections: Applicant's arguments regarding the 35 U.S.C. § 101 rejections of the previous office action have been fully considered, but are unpersuasive. Applicant asserts (Pages 13-14), that the amended independent claims include additional limitations that incorporate the alleged abstract idea into a practical application (see MPEP §2106.05) These amendments and improvements are discussed below with reference to amended claim 1 and similar independent claims. Claim 1 as amended claims a "method of down-sampling for imbalanced data." Where down-sampling improves model performance and is also supported within the specification. The amended independent claims provide an improvement over traditional down-sampling methods that can increase model accuracy through identification of "interesting" data groups and guided removal of harmful data groups. In addition to improving accuracy, the claimed method can reduce computational burden by evaluating group-level rather than record-level importance, guide better data curation in domains with noisy or mixed-quality data, and enhance model explainability through hierarchical record importance analysis and guidance (also supported within the specification). Applicant further asserts that as recited in amended claim 1, generating the record importance levels which is removing a group and rebuilding the model without the group reveals its impact on the accuracy (and supported within the specification). The claimed steps for down-sampling includes the importance evaluation which can identify "interesting" data groups and support down-sampling imbalanced data through importance-guided selection of groups (as noted within the specification). For at least the above reasons, Applicant respectfully asserts that claims 1-20 are not directed to a judicial exception and requests that the § 101 rejection be withdrawn. Examiner respectfully disagrees. The pending Claims are directed to a judicial exception due to reciting limitations which fall within the “mental processes” group of abstract ideas; where the judicial exception is unable to be directed to significantly more than the judicial exception due to the pending Claims not including additional elements that contribute to an “inventive concept”. The amended claims do not integrate the judicial exception into a practical application nor amount to significantly more . Although the Claims are interpreted in light of the specification, limitations from the specification are not read into the Claims. MPEP 2106.05(a) recites: After the examiner has consulted the specification and determined that the disclosed invention improves technology, the claim must be evaluated to ensure the claim itself reflects the disclosed improvement in technology … the claim must include the components or steps of the invention that provide the improvement described in the specification … It is important to note, the judicial exception alone cannot provide the improvement . The improvement can be provided by one or more additional elements . See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981)) in subsection II, below. Applicant fails to show how any alleged technical improvement would be provided by anything more than the judicial exception on its own. Additionally, applicant fails to show how the claim includes components or steps that would provide the alleged improvement described in the specification or by the cited case law. By MPEP 2106.05(f)(1), "the claim recites only the idea of a solution or outcome, i.e. the claim fails to recite details of how a solution to a problem is accomplished". Moreover, the examiner maintains that the Claim does not impose any meaningful limits on the judicial exceptions . As noted in the rejection, due to the additional elements falling under MPEP 2106.05, the judicial exception is not integrated into a practical application. Therefore, for the reasons given above and in the updated rejections below, the rejection to all Claims (including Claim 1 , analogous independent Claims, and all dependent Claims) are maintained and updated as necessitated by Claim amendments. Applicant’s arguments regarding the other independent and dependent claims rely upon the same assertions as with respect to Claim 1 , and are thus likewise unpersuasive. More specific details are discussed below within the 35 USC § 101 Rejections . Claim Objections Claims 5 , 12 , and 18 are objected to because of the following informalities: Claims 5 , 12 , and 18 recite “ … a first clustered data group being greater than the first trained model accuracy, the first clustered data group as less important than one or more of remaining clustered data groups ” which appears to be missing a term. Appropriate correction is required. For the purposes of examination, the limitation is being interpreted by the examiner as “ … a first clustered data group being greater than the first trained model accuracy, indicating the first clustered data group as less important than one or more of remaining clustered data groups ”. Duplicate Claims, Warning 07-05-05 Applicant is advised that should Claim 27 be found allowable, Claim 28 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m). Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 - 3 , 5 , 8 - 10 , 12 , 15 - 18 , and 21 - 28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Regarding Claim 1 : Subject Matter Eligibility Analysis Step 1: Claim 1 recites a method , thus a process, one of the four statutory categories of patentable subject matter. Subject Matter Eligibility Analysis Step 2A Prong 1: However, Claim 1 further recites the method comprising of: clustering … the training data to obtain a hierarchical tree comprising clustered data groups (a human being can mentally apply evaluation to cluster the training data to obtain a specific representation of the data) evaluating … importance of the clustered data groups, wherein the importance evaluation comprises … (a human being can mentally apply evaluation to evaluate the importance of the clustered data groups) generating … record importance levels for the clustered data groups, and wherein the generating the record importance levels comprises, for each clustered data group: (a human being can mentally apply evaluation to generate record importance levels on specific data) extracting … the clustered data group to produce first model test data that does not include the clustered data group … (a human being can mentally apply evaluation to extract a clustered data group from clustered data groups to produce a test data set for a first model) generating … based on a comparison between the first test data accuracy and the first trained model accuracy, a record importance level corresponding to the clustered data group (a human being can mentally apply evaluation to generate based on a comparison between specific accuracies a record importance level associated with the clustered data group) identifying … based on the importance evaluation, interesting data groups from the clustered data groups (a human being can mentally apply evaluation to identify based on a importance evaluation metric interesting data groups from a set of clustered data groups) generating … based on the identifying, guidance for removing data from branches of the hierarchical tree to maintain data balance (a human being can mentally apply evaluation and make a judgement to generate instructions/guidance for removing data from branches of a hierarchical tree to maintain data balance) removing … in response to the receiving, the user-selected data groups from the training data (a human being can mentally apply evaluation to remove a clustered data group from a specific dataset based on an user selection) building … a second machine learning model … (a human being can mentally apply evaluation to build a machine learning model) Claim 1 thus recites an abstract idea (that falls into the “mental processes” group of abstract ideas). Subject Matter Eligibility Analysis Step 2A Prong 2: This judicial exception is not integrated into a practical application because the additional elements recited consists of: A computer-implemented method of down-sampling for imbalanced data, the method comprising: (which is restricting the abstract idea to a Particular Technological Environment, by MPEP 2106.05(h)) receiving … training data and test data (which is insignificant extra-solution activity of data gathering, by MPEP 2106.05(g)) … by one or more processors and from a database … (to perform a mental process and the performance of an abstract idea on a computer is no more than instructions to “apply it” on a computer, by MPEP 2106.05(f)) training … a first model on the training data to obtain a first trained model having a first trained model accuracy measured on the test data (to perform a mental process and the performance of an abstract idea on a computer is no more than instructions to “apply it” on a computer, by MPEP 2106.05(f)) processing … the first model test data using the first trained model to generate first trained model output data having a first test data accuracy (to perform a mental process and the performance of an abstract idea on a computer is no more than instructions to “apply it” on a computer, by MPEP 2106.05(f)) generating … a hierarchical cluster data view illustrating the guidance and the clustered data groups and their corresponding record importance levels on a user interface (which is insignificant extra-solution activity of data display or output, by MPEP 2106.05(g)) receiving … a user selection of data groups to be removed from the hierarchical tree entered via the user interface in response to the hierarchical cluster data view (which is insignificant extra-solution activity of data gathering, by MPEP 2106.05(g)) … the second machine learning model trained on the training data excluding the removed data groups (to perform a mental process and the performance of an abstract idea on a computer is no more than instructions to “apply it” on a computer, by MPEP 2106.05(f)) Subject Matter Eligibility Analysis Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements recited, alone or in combination, do not provide significantly more than the abstract idea itself. Additional element a is only restricting the abstract idea to a Particular Technological Environment (MPEP 2106.05(h)) which cannot provide significantly more. Additional elements b and g fall within MPEP 2106.05(d) as well-understood, routine and conventional activities of receiving or transmitting data over a network ( MPEP 2106.05(d)(II): buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) ). Additional element f falls within MPEP 2106.05(d) as well-understood, routine and conventional activities of presenting offers and gathering statistics (MPEP 2106.05(d)(II): OIP Techs., 788 F.3d at 1362- 63, 115 USPQ2d at 1092-93 ). Additional elements c - e , and h are merely applying the abstract idea on a computer (MPEP 2106.05(f)) which cannot provide significantly more. Thus, the claim is subject-matter ineligible . Regarding Claim 2 : Subject Matter Eligibility Analysis Step 1: Dependent Claim 2 recites the method of Claim 1 . Claim 1 is a method, thus a process, one of the four statutory categories of patentable subject matter. Subject Matter Eligibility Analysis Step 2A Prong 1: However, Claim 2 does not recite any additional abstract ideas and only inherits the abstract ideas from Claim 1 . Claim 2 thus recites an abstract idea (that falls into the “mental processes” group of abstract ideas). Subject Matter Eligibility Analysis Step 2A Prong 2: This judicial exception is not integrated into a practical application because the new sole additional element recited consists of wherein the clustering the training data comprises: processing … the training data using hierarchical clustering to group the training data into the clustered data groups based on one or more features corresponding to a hierarchy of importance (to perform a mental process and the performance of an abstract idea on a computer is no more than instructions to “apply it” on a computer, by MPEP 2106.05(f)). Subject Matter Eligibility Analysis Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the new sole additional element recited, alone or in combination, does not provide significantly more than the abstract idea itself. The additional element is only restricting the abstract idea to a Particular Technological Environment (MPEP 2106.05(h)) which cannot provide significantly more. Thus, the claim is subject-matter ineligible . Regarding Claim 3 : Subject Matter Eligibility Analysis Step 1: Dependent Claim 3 recites the method of Claim 1 . Claim 1 is a method, thus a process, one of the four statutory categories of patentable subject matter. Subject Matter Eligibility Analysis Step 2A Prong 1: However, Claim 3 further recites the method comprising of wherein the extracting the clustered data group comprises: applying … a leave-one-out method to the clustered data groups to remove one of the clustered data groups at a time, wherein the first model test data includes a remaining set of the clustered data groups excluding the first clustered data group (a human being can mentally apply evaluation to make a judgement for applying a method for removing clustered data groups in a specific manner with specific data/restriction). Claim 3 thus recites an abstract idea (that falls into the “mental processes” group of abstract ideas). Subject Matter Eligibility Analysis Step 2A Prong 2: This judicial exception is not integrated into a practical application because there are no new additional elements recited. Subject Matter Eligibility Analysis Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because there are no new additional elements recited. The judicial exception alone does not provide significantly more than the abstract idea itself. Thus, the claim is subject-matter ineligible . Regarding Claim 5 : Subject Matter Eligibility Analysis Step 1: Dependent Claim 5 recites the method of Claim 1 . Claim 1 is a method, thus a process, one of the four statutory categories of patentable subject matter. Subject Matter Eligibility Analysis Step 2A Prong 1: However, Claim 5 further recites the method comprising of wherein the generating the hierarchical cluster data view comprises, based on the first test data accuracy for a first clustered data group being greater than the first trained model accuracy, the first clustered data group as less important than one or more of remaining clustered data groups (a human being can mentally apply evaluation to label clustered data groups with a record importance label noting a cluster to be less important based on a threshold). Claim 5 thus recites an abstract idea (that falls into the “mental processes” group of abstract ideas). Subject Matter Eligibility Analysis Step 2A Prong 2: This judicial exception is not integrated into a practical application because there are no new additional elements recited. Subject Matter Eligibility Analysis Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because there are no new additional elements recited. The judicial exception alone does not provide significantly more than the abstract idea itself. Thus, the claim is subject-matter ineligible . Regarding Claim 21 : Subject Matter Eligibility Analysis Step 1: Dependent Claim 21 recites the method of Claim 1 . Claim 1 is a method, thus a process, one of the four statutory categories of patentable subject matter. Subject Matter Eligibility Analysis Step 2A Prong 1: However, Claim 21 further recites the method comprising of classifying … based on the importance evaluation, each of the interesting data groups as harmful or beneficial to prediction accuracy (a human being can mentally apply evaluation to make a judgement for classifying based on importance evaluations specific data groups as either harmful or beneficial to prediction accuracy). Claim 21 thus recites an abstract idea (that falls into the “mental processes” group of abstract ideas). Subject Matter Eligibility Analysis Step 2A Prong 2: This judicial exception is not integrated into a practical application because there are no new additional elements recited. Subject Matter Eligibility Analysis Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because there are no new additional elements recited. The judicial exception alone does not provide significantly more than the abstract idea itself. Thus, the claim is subject-matter ineligible . Regarding Claim 22 : Subject Matter Eligibility Analysis Step 1: Dependent Claim 22 recites the method of Claim 1 . Claim 1 is a method, thus a process, one of the four statutory categories of patentable subject matter. Subject Matter Eligibility Analysis Step 2A Prong 1: However, Claim 22 further recites the method comprising of … based on the importance evaluation, removing data groups that decrease, maintain, or increase model accuracy based on user-selected model parameters (a human being can mentally apply evaluation to make a judgement based on importance evaluations to remove data groups that decrease, maintain, or increase model accuracy). Claim 22 thus recites an abstract idea (that falls into the “mental processes” group of abstract ideas). Subject Matter Eligibility Analysis Step 2A Prong 2: This judicial exception is not integrated into a practical application because there are no new additional elements recited. Subject Matter Eligibility Analysis Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because there are no new additional elements recited. The judicial exception alone does not provide significantly more than the abstract idea itself. Thus, the claim is subject-matter ineligible . Regarding Claim 23 : Subject Matter Eligibility Analysis Step 1: Dependent Claim 23 recites the method of Claim 1 . Claim 1 is a method, thus a process, one of the four statutory categories of patentable subject matter. Subject Matter Eligibility Analysis Step 2A Prong 1: However, Claim 23 further recites the method comprising of wherein the identifying comprises identifying interesting data groups in each level or branch of the hierarchical tree (a human being can mentally apply evaluation to identify specific interesting groups for each level/branch of a tree). Claim 23 thus recites an abstract idea (that falls into the “mental processes” group of abstract ideas). Subject Matter Eligibility Analysis Step 2A Prong 2: This judicial exception is not integrated into a practical application because there are no new additional elements recited. Subject Matter Eligibility Analysis Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because there are no new additional elements recited. The judicial exception alone does not provide significantly more than the abstract idea itself. Thus, the claim is subject-matter ineligible . Regarding Claims 8 - 10 , 12 , and 24 - 26 : Claims 8 - 10 , 12 , and 24 - 26 incorporate substantively all the limitations of Claims 1 - 3 , 5 , and 21 - 23 in a computer program product comprising of a computer readable storage media (thus, a manufacture) and further recites one or more computer readable storage media and program instructions collectively stored on the one or more computer readable storage media, the program instructions comprising (these claim limitations appear to perform a mental process and the performance of an abstract idea on a computer is no more than instructions to “apply it” on a computer, by MPEP 2106.05(f)) and does not appear to integrate the abstract idea into a particular application; thus, the claim is subject -matter ineligible as it does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, alone or in combination, do not provide significantly more than the abstract idea itself); thus, Claims 8 - 10 , 12 , and 24 - 26 are rejected for reasons set forth in the rejections of Claims 1 - 3 , 5 , and 21 - 23 , respectively. Regarding Claims 15 - 18 , and 27 - 28 : Claims 15 - 18 , and 27 - 28 incorporate substantively all the limitations of Claims 1 - 3 , 5 , and 21 - 21 (please note the duplicate claims warning above for Claims 27 - 28 ), in a computer system (thus, a machine) and further recites one or more computer processors; one or more computer readable storage media; and program instructions collectively stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the program instructions comprising (these claim limitations appear to perform a mental process and the performance of an abstract idea on a computer is no more than instructions to “apply it” on a computer, by MPEP 2106.05(f)) and does not appear to integrate the abstract idea into a particular application; thus, the claim is subject -matter ineligible as it does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, alone or in combination, do not provide significantly more than the abstract idea itself); thus, Claims 15 - 18 , and 27 - 28 are rejected for reasons set forth in the rejections of Claims 1 - 3 , 5 , and 21 - 21 , respectively. Examiner Comments The claims have been searched but no prior art which anticipates or renders the listed dependent claims as obvious have been found. Independent Claims 1 , 8 , and 15 are currently rejected under 35 USC § 101 only. A complete and thorough search was performed for these claims; however no prior art was uncovered that teach or fairly suggest the features recited claims. Specifically, none of the prior art of record, either alone or in combination, fairly discloses the limitations of the Independent Claims 1 , 8 , and 15 . In particular, the limitations in (underlined to show emphasis): Claims 1 , 8 , and 15 : A computer-implemented method of down-sampling for imbalanced data , the method comprising: … evaluating, by the one or more processors, importance of the clustered data groups, wherein the importance evaluation comprises generating , by the one or more processors, record importance levels for the clustered data groups in training data, and wherein the generating the record importance levels comprises, for each clustered data group: …; and generating, by the one or more processors and based on a comparison between the first test data accuracy and the first trained model accuracy , a record importance level corresponding to the clustered data group ; … generating , by the one or more processors and based on the identifying, guidance for removing data from branches of the hierarchical tree to maintain data balance; … The closest prior arts of record are: Meredig et al., “Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery”, which discloses utilizing LOCO-CV (Leave One Cluster Out Cross Validation) which is a cross validation technique and not a down-sampling methodology as cluster importance is determined on clusters left out but not removed completely. Hancock et al., “Supervised Hierarchical Clustering Using CART”, discloses cross validation classification rates, cluster generation/evaluations, and hierarchical cluster analysis Nevertheless, Meredig / Hancock in combination do not teach down sampling and receiving user selection and removing data groups. However, Brandt et al., “Interactive Clustering for Data Exploration” teaches hierarchical cluster data views for interactions. However, Meredig / Hancock / Brandt in combination do not teach down-sampling for imbalanced data and generating record importance level for each cluster data group in the steps recited within the independent claim and underlined above. The combination of these three prior arts do not disclose the expression defined in Claim 1 and it’s dependent claims. Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure : Meredig et al., “Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery”. Hancock et al., “Supervised Hierarchical Clustering Using CART”, Brandt et al., “Interactive Clustering for Data Exploration”. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL . See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to IBRAHIM RAHMAN whose telephone number is (703)756-1646. The examiner can normally be reached M-F 8am-5pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kakali Chaki can be reached at (571) 272-3719. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /I.R./ Examiner, Art Unit 2122 /KAKALI CHAKI/ Supervisory Patent Examiner, Art Unit 2122 Application/Control Number: 17/465,018 Page 2 Art Unit: 2122 Application/Control Number: 17/465,018 Page 3 Art Unit: 2122 Application/Control Number: 17/465,018 Page 4 Art Unit: 2122 Application/Control Number: 17/465,018 Page 5 Art Unit: 2122 Application/Control Number: 17/465,018 Page 6 Art Unit: 2122 Application/Control Number: 17/465,018 Page 7 Art Unit: 2122 Application/Control Number: 17/465,018 Page 8 Art Unit: 2122 Application/Control Number: 17/465,018 Page 9 Art Unit: 2122 Application/Control Number: 17/465,018 Page 10 Art Unit: 2122 Application/Control Number: 17/465,018 Page 11 Art Unit: 2122 Application/Control Number: 17/465,018 Page 12 Art Unit: 2122 Application/Control Number: 17/465,018 Page 13 Art Unit: 2122 Application/Control Number: 17/465,018 Page 14 Art Unit: 2122 Application/Control Number: 17/465,018 Page 15 Art Unit: 2122 Application/Control Number: 17/465,018 Page 16 Art Unit: 2122 Application/Control Number: 17/465,018 Page 17 Art Unit: 2122 Application/Control Number: 17/465,018 Page 18 Art Unit: 2122
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