List of Articles Effective features

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  1 - Nonparametric model test by using adaptive group LASSO method to identify the effective features in predicting the expected returns of stock portfolios
  Raheleh ossadat Mortazavi Hamidreza Vakilifard Ghodratallah Talebnia seyedeh mahboobeh jafari
  In this paper, a new nonparametric method is applied using the adaptive group LASSO for selecting features and studying which of the features provide incremental information for predicting the cross-sectional expected return. Out of many features mentioned in previous s More

  In this paper, a new nonparametric method is applied using the adaptive group LASSO for selecting features and studying which of the features provide incremental information for predicting the cross-sectional expected return. Out of many features mentioned in previous studies, the effect of 36 characteristics on the expected returns of stock portfolios in Tehran Stock Exchange (1396-1387) was investigated.The result of this study shows that only three to five features provide incremental information to predict the expected return on stock portfolios. Therefore, only the return characteristics of 2 to 1 month before the forecast, total fluctuations, beta, maximum daily returns, and the ratio of price to the highest price have the power to predict the expected return on stock portfolios. The rest of the studied features do not have the power to predict expected returns. Manuscript profile
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  2 - An Ensemble Classifier Method for Breast Cancer Detection Using Genetic Algorithm and Multistage Adjustment of Weights in the MLP Neural Network
  Amin Rezaeipanah S. J. Mirabedini ali mobaraki
  Today, with the increasing spread of science, the use of decision support systems can be of great help in the therapeutic policies of the Doctor. For this purpose, the use of artificial intelligence systems in predicting and diagnosing breast cancer, which is one of the More

  Today, with the increasing spread of science, the use of decision support systems can be of great help in the therapeutic policies of the Doctor. For this purpose, the use of artificial intelligence systems in predicting and diagnosing breast cancer, which is one of the most common cancers among women, is being considered. In this study, the process of diagnosis of breast cancer is done by using multistage weights in the MLP neural network in two layers. In the first layer, the three classifiers are trained simultaneously on the learning set data. Upon completion of the training, the output of the classifier of the first layer is accumulated together with the learning set data in the new sets. This set is given as an input to the second layer superconductor, and the supra-class mapping maps between the outputs of each of the ordinary classifiers of the first layer with the actual output classes. The three-layer structure of the first layer, as well as the second-layer supraclavicle, is a MLP neural network that optimizes the weights, effective properties and the size of the hidden layer simultaneously using an innovative genetic algorithm. In order to evaluate the accuracy of the proposed model, the Wisconsin database is used, which was created by the FNA test. Experiment results on the WBCD dataset the accuracy is 98.72% for the proposed method, which is relative to GAANN, CAFS algorithms provide better performance. Manuscript profile
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  3 - The Analysis of Effective Features in EducationalPrograms in the Agricultural Sector
  Mohammad Ali Nadi Narges KeshtiaraY Ramezan Jahanian Mozhgani Arefi Shahin Raz Masoud Salimi Arsalan. ErajiRad. Nozhatozamani Moshfeghi AliReza Uosefi Fariba Karimi Seyed Ali t Siyadat Shahram Shahbazi Hamideh Goharan
  Abstract Executing different educational programs with respect to the structure and tasks of the Ministry of Agricultural Jihad in order to update the knowledge and skills of staff is one of the primary tasks of the Research and Education Organization. This study ai More

  Abstract Executing different educational programs with respect to the structure and tasks of the Ministry of Agricultural Jihad in order to update the knowledge and skills of staff is one of the primary tasks of the Research and Education Organization. This study aims at analyzing and formulating effective features in educational programs in the agricultural sector. In so doing, the following two questions about formulating effective features in educational programs in the agricultural sector were asked of the teaching and research staff and educational experts of the Ministry of Agricultural Jihad. 1. What are the effective features of educational programs in agricultural sector? 2. Which of the identified features to promote the effectivity of the presented model of educational programs are of more importance? This research is descriptive and survey – based. The statistical community, a total of 383 people, were the teaching /research staff, instructors, educational directors, and experts o the Ministry of Agricultural Jihad. Data – collection and measurement tools at this study were researcher – tailored. Data analysis was conducted on two levels of descriptive statistics (frequency, mean, standard deviation) and inferential statistics (t– tests, multi – variable regression, and path analysis diagram). Manuscript profile