Predicting the cost of development effort is essential for successful projects. This helps software project managers to allocate resources, and determine budget or delivery date. paper evaluates a set machine learning algorithms techniques in predicting A feature selection algorithm utilized enhance accuracy prediction process. evaluations are presented based on basic classifiers stacked ensemb...

The right and left hand Motor Imagery (MI) analysis based on the electroencephalogram (EEG) signal can directly link the central nervous system to a computer or a device. This study aims to identify a set of robust and nonlinear effective brain connectivity features quantified by transfer entropy (TE) to characterize the relationship between brain regions from EEG signals and create a hierarchi...

Abstract We propose a novel technique for algorithm-selection, applicable to optimisation domains in which there is implicit sequential information encapsulated the data, e.g., online bin-packing. Specifically we train two types of recurrent neural networks predict packing heuristic bin-packing, selecting from four well-known heuristics. As input, RNN methods only use sequence item-sizes. This ...

Abstract Sample correlations and feature relations are two pieces of information that needed to be considered in the unsupervised selection, as labels missing guide model construction. Thus, we design a novel selection scheme, this paper, via considering completed sample dependencies unified framework. Specifically, self-representation graph construction conducted preserve select important neig...

breast cancer is the most common type of cancer among women. the important key to treat the breast cancer is early detection of it because according to many pathological studies more than 80% of all abnormalities are still benign at primary stages; so in recent years, many studies and extensive research done to early detection of breast cancer with higher precision and accuracy.infra-red breast...

The demand for mass custom parts is increasing, estimating the cost of to a high degree efficiency matter great concern most manufacturing companies. Under premise machining operations, estimation based on features and processes yields accuracy, but it necessitates accurately identifying part’s establishing relationship between feature cost. Accordingly, recognition method syntactic pattern pro...

Feature selection is a topic of great interest in applications dealing with high-dimensional datasets. These applications include gene expression array analysis, combinatorial chemistry and text processing of online documents. Using feature selection brings about several advantages. First, it leads to lower computational cost and time. Less memory is needed to store the data and less processing...

Abstract Introduction: Myocardial Infarction, also known as heart attack, normally occurs due to such causes as smoking, family history, diabetes, and so on. It is recognized as one of the leading causes of death in the world. Therefore, the present study aimed to evaluate the performance of classification models in order to predict Myocardial Infarction, using a feature selection method tha...

Feature selection is an e ective technique in dealing with dimensionality reduction for classi cation task a main component of data mining It searches for an optimal subset of features The search strategies under consideration are one of the three complete heuristic and probabilistic Existing algorithms adopt various measures to evaluate the goodness of feature subsets This work focuses on one ...