Many researchers proposed various models based on ANN but we did not find any estimation method focused on feature selection to remove the negative impact of irrelevant information. In this study, features with high information gain are selected using information gain to train the multilayer ...
Li L,Liu H,Ma Z,et al.Multi-label feature selectionvia information gain[M].Advanced data mining andapplications.[S.l.]:Springer International Publishing,2014:345-355.Li L, Liu H, Ma Z, Mo Y, Duan Z, Zhou J, Zhao J (2014) Multi-label feature selection via information gain. In: ...
Feature selection based on information gain. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 2(2):18-21, 2013.B. Azhagusundari and A. S. Thanamani, "Feature selection based on information gain," Int. J. Innovative Technol. Exploring Eng., vol. 2 pp. 2278...
Another popular feature selection technique is to calculate the information gain. You can calculate the information gain (also calledentropy) for each attribute for the output variable. Entry values vary from 0 (no information) to 1 (maximum information). Those attributes that contribute more informa...
Feature Selection in Text Categorization has usually been performed using a filtering approach based on selecting the features with highest score according to certain measures. Measures of this kind come from the Information Retrieval, Information Theory and Machine Learning fields. However, wrappe...
Feature selection should be one of the main concerns for a Data Scientist. Accuracy and generalization power can be leveraged by a correct feature selection, based in correlation, skewness, t-test, ANOVA, entropy and information gain. Many times a correct feature selection allows you to develop ...
To address this problem, this article introduces two new nonlinear feature selection methods, namely Joint Mutual Information Maximisation (JMIM) and Normalised Joint Mutual Information Maximisation (NJMIM); both these methods use mutual information and the ‘maximum of the minimum’ criterion, which ...
A comparative study of the three approaches is done using decision tree as classifier. The KDDcup 99 data set is used to train and test the decision tree classifiers. 展开 关键词: Decision trees Feature selection Filter method Chi square Information Gain ReliefF ...
1. Supervised Feature Selection Techniques Feature selection strategies in supervised learning aim to discover the most relevant features for predicting the target variable by using the relationship between the input features and the target variable. These strategies might help improve model performance, re...
Alhaj TA, Siraj MM, Zainal A, Elshoush HT, Elhaj F (2016) Feature selection using information gain for improved structural-based alert correlation. PLoS ONE 11(11):e0166017 Google Scholar Ali MH, Al Mohammed BAD, Ismail A, Zolkipli MF (2018a) A new intrusion detection system based ...