An Iterative Approach to the Feature Selection Problem
نویسندگان
چکیده
منابع مشابه
Ensemble Classification and Extended Feature Selection for Credit Card Fraud Detection
Due to the rise of technology, the possibility of fraud in different areas such as banking has been increased. Credit card fraud is a crucial problem in banking and its danger is over increasing. This paper proposes an advanced data mining method, considering both feature selection and decision cost for accuracy enhancement of credit card fraud detection. After selecting the best and most effec...
متن کاملOnline Streaming Feature Selection Using Geometric Series of the Adjacency Matrix of Features
Feature Selection (FS) is an important pre-processing step in machine learning and data mining. All the traditional feature selection methods assume that the entire feature space is available from the beginning. However, online streaming features (OSF) are an integral part of many real-world applications. In OSF, the number of training examples is fixed while the number of features grows with t...
متن کاملA Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization
Spam is an unwanted email that is harmful to communications around the world. Spam leads to a growing problem in a personal email, so it would be essential to detect it. Machine learning is very useful to solve this problem as it shows good results in order to learn all the requisite patterns for classification due to its adaptive existence. Nonetheless, in spam detection, there are a large num...
متن کاملIterative Approach for Automatic Beam Angle Selection in Intensity Modulated Radiation Therapy Planning
Introduction: Beam-angle optimization (BAO) is a computationally intensive problem for a number of reasons. First, the search space of the solutions is huge, requiring enumeration of all possible beam orientation combinations. For example, when choosing 4 angles out of 36 candidate beam angles, C36 = 58905 possible combinations exist. Second, any change in a beam 4 config...
متن کاملFuzzy-rough Information Gain Ratio Approach to Filter-wrapper Feature Selection
Feature selection for various applications has been carried out for many years in many different research areas. However, there is a trade-off between finding feature subsets with minimum length and increasing the classification accuracy. In this paper, a filter-wrapper feature selection approach based on fuzzy-rough gain ratio is proposed to tackle this problem. As a search strategy, a modifie...
متن کاملA New Iterative Neural Based Method to Spot Price Forecasting
Electricity price predictions have become a major discussion on competitive market under deregulated power system. But, the exclusive characteristics of electricity price such as non-linearity, non-stationary and time-varying volatility structure present several challenges for this task. In this paper, a new forecast strategy based on the iterative neural network is proposed for Day-ahead price...
متن کامل