Categorizing attire through the fashion MNIST dataset (Record no. 22439)
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| 000 -LEADER | |
|---|---|
| fixed length control field | a |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250311105637.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250311b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 25587 |
| Author | Kambham, Koushik |
| 245 ## - TITLE STATEMENT | |
| Title | Categorizing attire through the fashion MNIST dataset |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.3(1), Jan-Apr |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Ghaziabad |
| Name of publisher, distributor, etc. | MAT Journals |
| Year | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 14-20p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | The ongoing expansion of the online fashion market is leading fashion websites to accumulate increasing volumes of data from diverse brands. Consequently, the task of classifying various garments has become challenging for numerous websites. Addressing this challenge necessitates the implementation of a highly accurate algorithm capable of identifying garments. Such an algorithm can prove instrumental for companies in the clothing sales sector, aiding in comprehending the profiles of potential buyers. It enables businesses to tailor their sales strategies to specific niches, develop targeted campaigns aligned with customer preferences, and enhance overall user experience. This project is aimed to find the best model with the highest accuracy and precision results. Models like Logistic Regression, Decision Tree Classifier, Random Forest Classifier and some other models are used in this project to classify the garments. To train and test these models, the Fashion MNIST dataset is used. Among all the models that are used here, the model that shows the best performance is suggested to the fashion website. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 22400 |
| Topical term or geographic name entry element | Data Science |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 25531 |
| Co-Author | Sreekala, K. |
| 773 0# - HOST ITEM ENTRY | |
| Title | Journal of innovations in data science and big data management |
| Place, publisher, and date of publication | Ghaziabad MAT Journals |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | https://matjournals.net/engineering/index.php/JIDSBDM/article/view/95 |
| Link text | Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Articles Abstract Database |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | School of Engineering & Technology | School of Engineering & Technology | Archieval Section | 11/03/2025 | 2025-0351 | 11/03/2025 | 11/03/2025 | Articles Abstract Database |