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Found 13 papers, 0 papers with code
Predicting students' learning styles using regression techniques
One of the personalization methods is detecting the learners' learning style.
Application of Machine Learning for Online Reputation Systems
Furthermore, the performance of the proposed model has been compared to previous published rating aggregation models.
Examining stability of machine learning methods for predicting dementia at early phases of the disease
To examine the stability of these algorithms, thresholds of feature selection were changed for the IG from 20% to 100% and the PCA dimension from 2 to 8.
An Interactive Automation for Human Biliary Tree Diagnosis Using Computer Vision
This study is unique in that it uses an automated approach to segment the biliary tree from MRI images, as well as scientifically correlating retrieved features with biliary tree status that has never been done before in the literature.
Artificial Intelligence and Statistical Techniques in Short-Term Load Forecasting: A Review
The most successful duration for short-term forecasting has been identified as prediction for a duration of one day at an hourly interval.
Empirical Analysis on Productivity Prediction and Locality for Use Case Points Method
This paper examines the impact of data locality approaches on productivity and effort prediction from multiple UCP variables.
Software Engineering
Ensemble of Learning Project Productivity in Software Effort Based on Use Case Points
It is well recognized that the project productivity is a key driver in estimating software project effort from Use Case Point size metric at early software development stages.
v-SVR Polynomial Kernel for Predicting the Defect Density in New Software Projects
Statistical significance test showed that v-SVR with polynomial kernel was better than that of SLR when new software projects were developed on mainframes and coded in programming languages of third generation
A Comparative Study for Predicting Heart Diseases Using Data Mining Classification Methods
In this context, five data mining classifying algorithms, with large datasets, have been utilized to assess and analyze the risk factors statistically related to heart diseases in order to compare the performance of the implemented classifiers (e. g., Na\"ive Bayes, Decision Tree, Discriminant, Random Forest, and Support Vector Machine).
Fuzzy Model Tree For Early Effort Estimation
Use Case Points (UCP) is a well-known method to estimate the project size, based on Use Case diagram, at early phases of software development.
Learning best K analogies from data distribution for case-based software effort estimation
In this paper we propose a new technique based on Bisecting k-medoids clustering algorithm to better understanding the structure of a dataset and discovering the the optimal cases for each individual project by excluding irrelevant cases.
Pareto Efficient Multi Objective Optimization for Local Tuning of Analogy Based Estimation
Therefore, the main theme of this research is how to come up with best decision variables that improve adaptation strategy and thus, the overall evaluation measures without degrading the others.
A Comparison Between Decision Trees and Decision Tree Forest Models for Software Development Effort Estimation
Accurate software effort estimation has been a challenge for many software practitioners and project managers.
