WO2024019697 - DECISION TREE ALGORITHMS IN MACHINE LEARNING TO LEARN AND TO PREDICT INNOVATIONS
National phase entry:
Publication Number
WO/2024/019697
Publication Date
25.01.2024
International Application No.
PCT/US2022/000013
International Filing Date
19.07.2022
Title **
[English]
DECISION TREE ALGORITHMS IN MACHINE LEARNING TO LEARN AND TO PREDICT INNOVATIONS
[French]
ALGORITHMES D'ARBRE DE DÉCISION DANS L'APPRENTISSAGE AUTOMATIQUE POUR APPRENDRE ET PRÉDIRE DES INNOVATIONS
Applicants **
MARGUERITE, Johnson
Inventors
MARGUERITE, Johnson
Application details
| Total Number of Claims/PCT | * |
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| Number of Drawings | * |
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International Searching Authority |
USPTO
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| Recordal of a Change of the Applicant's Name/Address |
Change of Applicant's Name and Address
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| Type of Assignment |
The Standard Agent's Assignment
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| Applicant's Legal Status |
Natural Person
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| Entry into National Phase under |
Chapter II
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| Patent Delivery |
Send the Letters Patent by Courier
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| 译文 |
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** IP-Coster compiles data from publicly available sources. If this data includes your personal information, you can contact us to request its removal.
Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing, Examination, Granting | 2982 | |
| EPO | Filing, Examination, Granting | 20502 | |
| Japan | Filing, Examination, Granting | 3173 | |
| South Korea | Filing, Examination, Granting | 4239 | |
| USA | Filing, Examination, Granting | 21310 |
Total:
52,206
The term for entry into the National Phase has expired. This quotation is for informational purposes only
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Abstract[English]
Decision Tree Algorithms that learn by training on datasets and models of innovations with Target Variables, Proximal Variables, Nodes, and Parameters to create predictive models. Decision Tree Algorithms can be configured to train on datasets and models of information describing, classifying, and categorizing innovations. Potentially, Decision Tree Algorithms unlock innovations hidden within historical records, specifications, reports, analyses, relationships, adjacencies, applications, products, business models, patent applications, systems, components, lab results, and other information.[French]
Algorithmes d'arbre de décision qui apprennent par entraînement sur la base de jeux de données et de modèles d'innovations avec des variables cibles, des variables proximales, des nœuds et des paramètres pour créer des modèles prédictifs. Des algorithmes d'arbre de décision peuvent être configurés pour réaliser un entraînement sur la base de jeux de données et de modèles d'informations décrivant, classifiant et catégorisant des innovations. Potentiellement, des algorithmes d'arbre de décision déverrouillent des innovations cachées dans des enregistrements historiques, des spécifications, des rapports, des analyses, des relations, des contiguïtés, des applications, des produits, des modèles commerciaux, des applications de brevet, des systèmes, des composants, des résultats de laboratoire et d'autres informations.