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An ensemble feature selection method to detect web spam
Published 2018“…In addition, it improves classification metrics in comparison to basic feature selection methods.…”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach
Published 2001“…Using the developed algorithm, the safety measures involved are such as reliability index and the probability of failure; instead of only factor of safety if conventional deterministic approach is used. …”
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Discriminative feature representation for Malay children’s speech recognition / Seyedmostafa Mirhassani
Published 2015“…In case of multiple filterbanks the cepstral features are used in different experts for performing classification based on different representation of speeches. …”
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Prediction Of Antimicrobial Peptides Based On Sequence Alignment And Secondary Structure Sequence And Segment Sequence.pdf
Published 2015“…The sequence alignment is accomplished by the classification of test sequences based on the maximum high-scoring segment pairs (HSPs) score predicted by Basic Local Alignment Search Tool for protein (BLASTP). …”
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