LEADER |
01931nam a22002297a 4500 |
001 |
2150218 |
041 |
|
|
|a eng
|
044 |
|
|
|b العراق
|
100 |
|
|
|a Salman, Nuha Ahmed
|e Author
|9 740196
|
245 |
|
|
|a A Developed Prediction Approach for Small Datasets
|
260 |
|
|
|b الجمعية العلمية للدراسات التربوية المستدامة
|c 2023
|g أغسطس
|m 1445
|
300 |
|
|
|a 759 - 774
|
336 |
|
|
|a بحوث ومقالات
|b Article
|
520 |
|
|
|b Using small datasets is a very challenging task. Developed approaches are significant to make accurate predictions, rankings and identify relevant attributes with a reliable model. Small dataset may lead to biased or incomplete models. Analyzing and prediction with small datasets is usually more difficult due to the restricted number of data. Identifying the relationships between the small dataset’s attributes, specific attributes may have a greater chance of ranking than others due to their insufficient availability. Machine learning has a flexibility and possibility to explain different prospects for health investigation when dealing with small datasets. This paper will analyze the difficulties in making predictions from small datasets and look at several strategies and algorithms that may be applied to reduce these difficulties and increase prediction accuracy
|
653 |
|
|
|a تكنولوجيا المعلومات
|a المعلومات الطبية
|a التعليم الآلي
|
692 |
|
|
|b Small Dataset
|b Prediction
|b Machine Learning
|b Attributes
|b Correlation
|
700 |
|
|
|9 740199
|a Hasson, Saad Talib
|e Co-Author
|
773 |
|
|
|4 التربية والتعليم
|6 Education & Educational Research
|c 033
|e Journal of Sustainable Studies
|f Mağallaẗ al-dirāsāt al-mustadāmaẗ
|l 988
|m مج5, ملحق
|o 2053
|s مجلة الدراسات المستدامة
|v 005
|x 2663-2284
|
856 |
|
|
|u 2053-005-988-033.pdf
|
930 |
|
|
|d y
|p y
|q y
|
995 |
|
|
|a EduSearch
|
999 |
|
|
|c 1399909
|d 1399909
|