Office Action Predictor
Last updated: April 17, 2026
Application No. 16/726,076

VISUALIZATION AND INTERACTION WITH COMPACT REPRESENTATIONS OF DECISION TREES

Non-Final OA §112
Filed
Dec 23, 2019
Examiner
MIAN, MUHAMMAD U
Art Unit
2163
Tech Center
2100 — Computer Architecture & Software
Assignee
Bigml, INC.
OA Round
9 (Non-Final)
67%
Grant Probability
Favorable
9-10
OA Rounds
2y 10m
To Grant
91%
With Interview

Examiner Intelligence

Grants 67% — above average
67%
Career Allow Rate
241 granted / 361 resolved
+11.8% vs TC avg
Strong +24% interview lift
Without
With
+24.3%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
20 currently pending
Career history
381
Total Applications
across all art units

Statute-Specific Performance

§101
21.7%
-18.3% vs TC avg
§103
46.4%
+6.4% vs TC avg
§102
7.8%
-32.2% vs TC avg
§112
16.9%
-23.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 361 resolved cases

Office Action

§112
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application is being examined under the pre-AIA first to invent provisions. Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 30 June 2025 has been entered. Response to Amendment This communication is in response to the amendment filed on 30 June 2025. Claims 1, 16, and 39 are amended. Claims 1, 3-5, 7-10, 13-16, 18-31, 33-35 and 37-39 have been examined. Response to Arguments In response to Applicant’s remarks filed on 30 June 2025: a. Rejections of the pending claims under 35 U.S.C. 112(a) are maintained. Independent claim 1 has been amended with the following newly-added limitations: generating a decision tree from plural instances of sample data, using a machine learning algorithm that builds a tree structure by analyzing the sample data; determining a number of instances in which the sample data corresponds to each of the nodes and the branches, by tracking how many data samples passed through each node during tree generation; in response to determining the number of instances, automatically pruning a portion of the nodes and the branches from the visualization based on significances of the nodes and the branches relative to the sample data, wherein the pruning removes nodes that received fewer than a threshold number of instances in the sample data to simplify the visualization while maintaining nodes that process larger portions of the data; wherein each question in the decision tree is assigned a unique color and all nodes representing different versions of that question throughout the tree are displayed in the same color to enable visual tracking of how the same question appears at different levels and branches of the tree; automatically adjusting widths of the branches remaining in the visualization based on the significances of the branches, wherein branch width visually represents a volume of sample data flowing through each path; providing an interface for the user to selectively prune a portion of the remaining nodes and the remaining branches through user controls that allow dynamic adjustment of visualization thresholds; and allowing the user to interact with any remaining nodes and any remaining branches in the visualization to display information pertaining to the sample data including displaying percentages indicating how much of the sample data reached each node. Independent claim 16 has been amended with the following newly-added limitations: generate a decision tree from the plural instances of the sample data by executing a tree generation algorithm that recursively partitions the sample data based on feature values; determine a number of instances in which the sample data corresponds to each of the nodes and the branches based on counting sample data instances that satisfied the conditions leading to each node during tree construction; in response to determining the number of instances, automatically prune a portion of the nodes and the branches from the visualization based on significances of the nodes and the branches relative to the sample data to reduce visual complexity while preserving the most important decision paths; wherein the color coding assigns the same color to all nodes that test the same underlying feature regardless of the specific threshold values or conditions, enabling a user to visually identify patterns of how specific features are used throughout different branches of the tree; automatically adjust widths of the branches remaining in the visualization based the significances of the branches such that branches carrying more sample data instances are displayed thicker than branches carrying fewer instances; provide an interface for the user to selectively prune a portion of the remaining nodes and the remaining branches including controls for hiding nodes based on importance thresholds and expanding or collapsing subtrees; and allow the user to interact with any remaining nodes and any remaining branches in the visualization to display information pertaining to the sample data, the information pertaining to the sample data including a percentage of sample data instances that were passed through a selected node, wherein selecting a node displays detailed statistics about the sample data that reached hat node including the percentage of total samples. Applicant has not indicated where support for this newly-added subject can be found, and Applicant’s specification does not appear to support the limitations as claimed. Hence, these newly-added limitations are deemed to introduce new matter. b. Applicant's arguments with respect to the 35 U.S.C. 103 rejections of the pending claims are withdrawn in view of Applicant’s amendments and arguments. Claim Objections Claim 16 is objected to because of the following informalities: Claim 16 recites the following: “wherein selecting a node displays detailed statistics about the sample data that reached hat node including the percentage of total samples.” The recitation of “hat node” appears to be a typographical error and it appears that the intended phrase is “that node.” Appropriate correction is required. Claim Rejections - 35 USC § 112 The following is a quotation of the first paragraph of 35 U.S.C. 112(a): (a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention. The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112: The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same and shall set forth the best mode contemplated by the inventor of carrying out his invention. Claims 1, 3-5, 7-10, 13-16, 18-31, 33-35 and 37-39 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. As to independent claim 1, the following limitations are newly-added: generating a decision tree from plural instances of sample data, using a machine learning algorithm that builds a tree structure by analyzing the sample data; determining a number of instances in which the sample data corresponds to each of the nodes and the branches, by tracking how many data samples passed through each node during tree generation; in response to determining the number of instances, automatically pruning a portion of the nodes and the branches from the visualization based on significances of the nodes and the branches relative to the sample data, wherein the pruning removes nodes that received fewer than a threshold number of instances in the sample data to simplify the visualization while maintaining nodes that process larger portions of the data; wherein each question in the decision tree is assigned a unique color and all nodes representing different versions of that question throughout the tree are displayed in the same color to enable visual tracking of how the same question appears at different levels and branches of the tree; automatically adjusting widths of the branches remaining in the visualization based on the significances of the branches, wherein branch width visually represents a volume of sample data flowing through each path; providing an interface for the user to selectively prune a portion of the remaining nodes and the remaining branches through user controls that allow dynamic adjustment of visualization thresholds; and allowing the user to interact with any remaining nodes and any remaining branches in the visualization to display information pertaining to the sample data including displaying percentages indicating how much of the sample data reached each node. Applicant has not indicated where support for this newly-added subject can be found, and Applicant’s specification does not appear to support the limitations as claimed. Hence, these newly-added limitations are deemed to introduce new matter. As to independent claim 16, the following limitations are newly-added: generate a decision tree from the plural instances of the sample data by executing a tree generation algorithm that recursively partitions the sample data based on feature values; determine a number of instances in which the sample data corresponds to each of the nodes and the branches based on counting sample data instances that satisfied the conditions leading to each node during tree construction; in response to determining the number of instances, automatically prune a portion of the nodes and the branches from the visualization based on significances of the nodes and the branches relative to the sample data to reduce visual complexity while preserving the most important decision paths; wherein the color coding assigns the same color to all nodes that test the same underlying feature regardless of the specific threshold values or conditions, enabling a user to visually identify patterns of how specific features are used throughout different branches of the tree; automatically adjust widths of the branches remaining in the visualization based the significances of the branches such that branches carrying more sample data instances are displayed thicker than branches carrying fewer instances; provide an interface for the user to selectively prune a portion of the remaining nodes and the remaining branches including controls for hiding nodes based on importance thresholds and expanding or collapsing subtrees; and allow the user to interact with any remaining nodes and any remaining branches in the visualization to display information pertaining to the sample data, the information pertaining to the sample data including a percentage of sample data instances that were passed through a selected node, wherein selecting a node displays detailed statistics about the sample data that reached hat node including the percentage of total samples. Applicant has not indicated where support for this newly-added subject can be found, and Applicant’s specification does not appear to support the limitations as claimed. Hence, these newly-added limitations are deemed to introduce new matter. As to dependent claims 3-5, 7-10, 13-15, 18-31, 33-35 and 37-39, they depend from claims 1 and 16, respectively, and these dependent claims inherit the deficiencies of their parent claims. The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 1, 3-5, 7-10, 13-16, 18-31, 33-35 and 37-39 are rejected 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. As to claim 1, the following is recited (emphasis added): “wherein the pruning removes nodes that received fewer than a threshold number of instances in the sample data to simplify the visualization while maintaining nodes that process larger portions of the data.” Prior to this, the claim introduces various types of data including “sample data” and “input data of a user.” The later recitation of “the data” is vague and ambiguous. For the purposes of examination, the limitation at issue will be interpreted as follows: “wherein the pruning removes nodes that received fewer than a threshold number of instances in the sample data to simplify the visualization while maintaining nodes that process larger portions of the sample data.” In addition, claim 1 recites the following (emphasis added): “wherein each question in the decision tree is assigned a unique color and all nodes representing different versions of that question throughout the tree are displayed in the same color to enable visual tracking of how the same question appears at different levels and branches at the tree.” The claim introduces a plurality of questions, and hence the later recitation of “the same question” is vague and ambiguous. For the purposes of examination, this limitation will be interpreted as follows: “wherein each question in the decision tree is assigned a unique color and all nodes representing different versions of that question throughout the tree are displayed in the same color to enable visual tracking of how each question appears at different levels and branches at the tree.” As to dependent claims 3-5, 7-10, 13-15, 33-35, and 39, they depend from claim 1 and therefore inherit its deficiencies. In addition, claim 4 recites the following: “further comprising: in the computing device, automatically identifying a subset of approximately 10-12 questions in the decision tree receiving largest numbers of instances of the sample data, without user input.” The claimed “approximately 10-12 questions” is relative terminology. The claims do not define approximately 10-12 questions, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Therefore, these claim limitations render the claims vague and ambiguous. See MPEP 2173.05(b). In addition, claim 9 recites the following: “wherein the predetermined maximum number of colors is equal to approximately 10.” The claimed “approximately 10” is relative terminology. The claims do not define approximately 10, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Therefore, these claim limitations render the claims vague and ambiguous. See MPEP 2173.05(b). As to claim 16, the following is recited (emphasis added): “determine a number of instances in which the sample data corresponds to each of the nodes and the branches based on counting sample data instances that satisfied the conditions leading to each node during tree construction.” There is insufficient antecedent basis for the highlighted limitation in this claim. In addition, the following is recited (emphasis added): “in response to determining the number of instances, automatically prune a portion of the nodes and the branches from the visualization based on significances of the nodes and the branches relative to the sample data to reduce visual complexity while preserving the most important decision paths.” There is insufficient antecedent basis for the highlighted limitation in this claim. In addition, the following is recited (emphasis added): “automatically color code the nodes remaining in the visualization by color coding a first node associated with a first version of a first question and a second node associated with a second version of the first question with a first color and color coding a plurality of third nodes associated with a second question with a second color, the first version and second version selected so that a range of answers are true for both the first version and the second version wherein the color coding assigns the same color to all nodes that test the same underlying feature regardless of the specific threshold values or conditions, enabling a user to visually identify patterns of how specific features are used throughout different branches of the tree;” and “allow the user to interact with any remaining nodes and any remaining branches in the visualization to display information pertaining to the sample data, the information pertaining to the sample data including a percentage of sample data instances that were passed through a selected node, wherein selecting a node displays detailed statistics about the sample data that reached hat node including the percentage of total samples.” There is insufficient antecedent basis for the above highlighted limitations in this claim. As to dependent claims 18-31 and 37-38, they depend from claim 16 and therefore inherit its deficiencies. Additional Art Considered The prior art made of record and not relied upon is considered pertinent to the Applicants’ disclosure. The following patents and papers are cited to further show the state of the art at the time of Applicants’ invention with respect to visualizing decision trees. a. Breslow, L.A. and Aha, D.W., 1997. Simplifying decision trees: A survey. Knowledge engineering review, 12(1), pp.1-40. Teaches that decision trees are “extensively researched” and that “For many practical tasks, the trees produced by tree-generation algorithms are not comprehensible to users due to their size and complexity” (see abstract). Teaches numerous techniques known in the academic literature for simplifying decision trees, including various tree pruning techniques (see Section 3: Tree-Simplification Approaches, pages 8-17). Teaches that “regions of the problem space with low frequencies of occurrence” are called “small disjuncts,” and “another reason for simplifying trees is to eliminate small disjuncts by pruning leaves having few cases” (see page 5, fourth full paragraph). Contact Information Any inquiry concerning this communication or earlier communications from the examiner should be directed to UMAR MIAN whose telephone number is (571)270-3970. The examiner can normally be reached Monday to Friday, 10 am to 6:30 pm. 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, Tony Mahmoudi can be reached on (571) 272-4078. 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. /Umar Mian/Examiner, Art Unit 2163
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Prosecution Timeline

Dec 23, 2019
Application Filed
Nov 09, 2020
Applicant Interview (Telephonic)
Nov 09, 2020
Examiner Interview Summary
Dec 08, 2020
Response after Non-Final Action
Apr 12, 2021
Response after Non-Final Action
May 21, 2021
Non-Final Rejection — §112
Sep 29, 2021
Interview Requested
Oct 13, 2021
Examiner Interview Summary
Oct 21, 2021
Response Filed
Dec 08, 2021
Final Rejection — §112
Jun 13, 2022
Request for Continued Examination
Jun 14, 2022
Response after Non-Final Action
Jun 30, 2022
Non-Final Rejection — §112
Oct 05, 2022
Response Filed
Dec 30, 2022
Final Rejection — §112
May 04, 2023
Request for Continued Examination
May 08, 2023
Response after Non-Final Action
May 17, 2023
Non-Final Rejection — §112
Nov 20, 2023
Response Filed
Feb 10, 2024
Final Rejection — §112
May 15, 2024
Request for Continued Examination
May 21, 2024
Response after Non-Final Action
Jun 13, 2024
Non-Final Rejection — §112
Sep 17, 2024
Response Filed
Dec 24, 2024
Final Rejection — §112
Jun 30, 2025
Request for Continued Examination
Jul 02, 2025
Response after Non-Final Action
Sep 18, 2025
Non-Final Rejection — §112
Apr 06, 2026
Response after Non-Final Action

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Prosecution Projections

9-10
Expected OA Rounds
67%
Grant Probability
91%
With Interview (+24.3%)
2y 10m
Median Time to Grant
High
PTA Risk
Based on 361 resolved cases by this examiner. Grant probability derived from career allow rate.

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