2,251 to 2,260 of 4,448 Results
Dec 1, 2020 -
The Neuroscience of Love
MPEG-4 Video - 47.5 MB -
MD5: b1546df3b3bad1b2b32a47d2813bb819
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Nov 14, 2020 -
Related Data for: A Machine Learning Approach For The Automatic Estimation Of Fixation-Time Data Signals’ Quality
Tabular Data - 28.3 KB - 38 Variables, 112 Observations - UNF:6:Ilgsr+/po2mt0okcjiWeRQ==
Database used for this study. |
Nov 14, 2020 -
Related Data for: A Machine Learning Approach For The Automatic Estimation Of Fixation-Time Data Signals’ Quality
Unknown - 603.8 KB -
MD5: a24fc06c9c4a792d684b960a490d3615
Dump of the trained classifier |
Nov 14, 2020 -
Related Data for: A Machine Learning Approach For The Automatic Estimation Of Fixation-Time Data Signals’ Quality
Unknown - 80.1 KB -
MD5: 279b1cc95325a44a08d61a20f5ffd7c7
Dump of the trained classifier |
Nov 14, 2020 -
Related Data for: A Machine Learning Approach For The Automatic Estimation Of Fixation-Time Data Signals’ Quality
Python Source Code - 11.7 KB -
MD5: 5e56391333eb91d9a1579c89fe05c523
Script used to train and test the classifiers on NTU's HPC Gekko cluster |
Nov 14, 2020 -
Related Data for: A Machine Learning Approach For The Automatic Estimation Of Fixation-Time Data Signals’ Quality
Unknown - 1.0 MB -
MD5: 32bad55a09af3c19e3a62f1d85828ad7
Dump of the trained classifier |
Nov 14, 2020 -
Related Data for: A Machine Learning Approach For The Automatic Estimation Of Fixation-Time Data Signals’ Quality
Plain Text - 1.6 KB -
MD5: cd1b9175bc06ba72c21557a2fbe2d672
Timestamped output file. |
Nov 14, 2020 -
Related Data for: A Machine Learning Approach For The Automatic Estimation Of Fixation-Time Data Signals’ Quality
Tabular Data - 401 B - 8 Variables, 3 Observations - UNF:6:urkJqTSw8q/YhkhNmar/Sw==
Scores (Accuracy, Precision, Recall, F1, MCC) of the three classifiers. |
Tabular Data - 3.2 KB - 9 Variables, 61 Observations - UNF:6:axvpY5/yK+xKuzewTN0Giw==
Database containing used data |
Plain Text - 647 B -
MD5: 265473eac141f8e42de20b7499efb6a4
Description of the dataset |
