1,121 to 1,130 of 1,574 Results
Aug 6, 2020 -
Related Data for: Machine Learning Estimation of users' Implicit and Explicit Aesthetic Judgments of Web-Pages
Unknown - 57.7 KB -
MD5: bef6c44a914a59cc6469c74ced5384ed
Trained model |
Aug 6, 2020 -
Related Data for: Machine Learning Estimation of users' Implicit and Explicit Aesthetic Judgments of Web-Pages
Unknown - 464.8 KB -
MD5: 2e98a9d030b5d7db1d28af4eca2818b9
Trained model |
Aug 6, 2020 -
Related Data for: Machine Learning Estimation of users' Implicit and Explicit Aesthetic Judgments of Web-Pages
Unknown - 194.6 KB -
MD5: b369782cc92471af610bd48601da7998
Trained model |
Aug 6, 2020 -
Related Data for: Machine Learning Estimation of users' Implicit and Explicit Aesthetic Judgments of Web-Pages
Python Source Code - 9.9 KB -
MD5: 43cdc698b89771ab0296381de5633a34
HPC Script for training and testing of the MLP model |
Aug 6, 2020 -
Related Data for: Machine Learning Estimation of users' Implicit and Explicit Aesthetic Judgments of Web-Pages
Plain Text - 1.7 KB -
MD5: 168f195c7ef96fc7735fcd32c0419513
HPC Output for training of explicit judgments models |
Aug 6, 2020 -
Related Data for: Machine Learning Estimation of users' Implicit and Explicit Aesthetic Judgments of Web-Pages
Plain Text - 1.3 KB -
MD5: f4353ae8c56efa06ad2fae4261dfc9a1
HPC Output for training of implicit judgments models |
Aug 6, 2020 -
Related Data for: Machine Learning Estimation of users' Implicit and Explicit Aesthetic Judgments of Web-Pages
Plain Text - 1.8 KB -
MD5: 96c02d3bf574c4a1f9f88b25387d5a3b
HPC Output for training of MLPmodel |
Aug 6, 2020 -
Related Data for: Machine Learning Estimation of users' Implicit and Explicit Aesthetic Judgments of Web-Pages
Tabular Data - 7.2 MB - 78 Variables, 8530 Observations - UNF:6:OXjgBp2o1P5HHQM/zPdxYA==
Physiological measures features database |
Aug 6, 2020 -
Related Data for: Machine Learning Estimation of users' Implicit and Explicit Aesthetic Judgments of Web-Pages
Comma Separated Values - 77.0 KB -
MD5: 3360d83d1cfc8941caad19e2f5d5ff6c
Website features database |
Tabular Data - 2.2 KB - 10 Variables, 58 Observations - UNF:6:3sn/pziJLhZ4n2PnYD0Iuw==
BONASSI ET AL., 2020
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# LEGEND #
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The dataset contains the following ten variables as columns:
1) "Gender" ("Male" | "Female")
2) "IG_posts" (Instagram number of published posts)
3) "IG_followers" (Instagram number of followers)
4) "IG_following"... |
