A SURVEY ON ANALYSIS AND PREDICTION OF DATA USING DATA SCIENCE
نویسندگان
چکیده
Intelligent technology development is gaining traction in the sphere of education. The increasing rise educational data suggests that standard processing methods may be limited and distorted. As a result, rebuilding mining research technologies education industry has become necessary. Becoming more visible To avoid erroneous assessment findings to anticipate students' future performance, this analyses predicts academic achievement using applicable clustering, discriminating, convolution neural network theories. begin, work clustering-number determination optimized by employing statistic never been employed K-means approach. clustering impact method next assessed discriminate analysis. Convolutional presented for training testing with labeled data. produced model can used forecast performance. Finally, efficacy constructed tested two metrics cross validation procedures order validate prediction findings. experimental show not only addresses objective quantitative problem determining number method, but also enhances predictability outcomes.
منابع مشابه
a study on insurer solvency by panel data model: the case of iranian insurance market
the aim of this thesis is an approach for assessing insurer’s solvency for iranian insurance companies. we use of economic data with both time series and cross-sectional variation, thus by using the panel data model will survey the insurer solvency.
pattern recognition in maintenance data using methodologies data minitng (cade study isfahan regional power electric company)
فعالیت های نگهداری و تعمیرات اطلاعاتی را تولید می کند که می تواند در تعیین زمان های بیکاری و ارایه یک برنامه زمان بندی شده یا تعیین هشدارهای خرابی به پرسنل نگهداری و تعمیرات کمک کند. وقتی که مقدار داده های تولید شده زیاد باشند، فهم بین متغیرها بسیار مشکل می شوند. این پایان نامه به کاربردی از داده کاوی برای کاوش پایگاه های داده چندبعدی در حوزه نگهداری و تعمیرات، برای پیدا کردن خرابی هایی که موجب...
15 صفحه اولAlert correlation and prediction using data mining and HMM
Intrusion Detection Systems (IDSs) are security tools widely used in computer networks. While they seem to be promising technologies, they pose some serious drawbacks: When utilized in large and high traffic networks, IDSs generate high volumes of low-level alerts which are hardly manageable. Accordingly, there emerged a recent track of security research, focused on alert correlation, which ext...
متن کاملAccuracy Improvement of Mood Disorders Prediction using a Combination of Data Mining and Meta-Heuristic Algorithms
Introduction: Since the delay or mistake in the diagnosis of mood disorders due to the similarity of their symptoms hinders effective treatment, this study aimed to accurately diagnose mood disorders including psychosis, autism, personality disorder, bipolar, depression, and schizophrenia, through modeling and analyzing patients' data. Method: Data collected in this applied developmental resear...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International journal of engineering technology and management sciences
سال: 2023
ISSN: ['2581-4621']
DOI: https://doi.org/10.46647/ijetms.2023.v07i02.068