Combining MLC and SVM classifiers for learning based decision making: analysis and evaluations
Citations
137 citations
Cites methods from "Combining MLC and SVM classifiers f..."
...(1) SVM: SVM is the conventional shallow structured classifier [Zhang et al. 2015a] and is set as the baseline for comparisons....
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...We compare the proposed generalized DTNs (sig-tDTNs and duft-tDTNs) to the following methods: (1) SVM: SVM is the conventional shallow structured classifier [Zhang et al. 2015a] and is set as the baseline for comparisons....
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130 citations
Cites methods from "Combining MLC and SVM classifiers f..."
...For regression purpose, a linear SVM is adopted for its simplicity and effectiveness[23][102]....
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128 citations
Cites methods from "Combining MLC and SVM classifiers f..."
...There were many popular algorithms concerning about Classifier Combination; such as Bayesian [41], [42], Dempster–Shafer [43]–[47], Fuzzy Integral [48], [49], and Voting Methods [50]–[57]....
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23 citations
Additional excerpts
...[56] and Szuster et al....
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19 citations
Cites background or methods from "Combining MLC and SVM classifiers f..."
...…impact of urban impervious surfaces on environmental issues such as water and air pollution, flooding, and urban climate, the amount of impervious surfaces (IS) has been recognized as the most significant index of environmental quality (Arnold Jr and Gibbons 1996; Weng 2012; Zhang et al. 2015a)....
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...…it is also reported that the distribution of IS plays a crucial role in estimating numerous socioeconomic factors such as urban development, population distribution and density, social conditions, and fluctuation of housing prices (Wu and Murray 2003; Yuan and Bauer 2007; Zhang et al. 2015a)....
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...This algorithm is based on Bayesian theory in estimating parameters of a probabilistic model (Zhang et al. 2015b)....
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...Nevertheless, accuratemapping of impervious surfaces using satellite passive sensor data has been a challenging task due to the diversity of urban land cover classes, where confusion often occurs between pervious and impervious surfaces (Weng 2012; Zhang et al. 2015a, 2016; Ma et al. 2017b)....
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...A number of studies on the extraction of IS, including Slonecker et al. (2001), Bauer et al. (2005), Yuan and Bauer (2007), Weng (2012), Wang et al. (2015), Zhang et al. (2015a), and Wei and Blaschke (2018), have shown the effectiveness and reliability of remote sensing in the monitoring of UIS....
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References
1,580 citations
"Combining MLC and SVM classifiers f..." refers methods in this paper
...Taking the application in remote sensing for example, in Pal and Mather [12] and Huang et al [13], it is found SVM outperforms MLC and several other classifiers....
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1,032 citations
1,010 citations
"Combining MLC and SVM classifiers f..." refers background in this paper
...On the other hand, support vector machines (SVM) have attracted much increasing attention, which can be found in almost all areas when prediction and classification of signal are required, such as scour prediction on grade-control structure [7], fault diagnosis [8], EEG signal classification [9], and fire detection [10] as well as road sign detection and recognition [11]....
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926 citations
"Combining MLC and SVM classifiers f..." refers background in this paper
...In addition, in Lin et al [27] Platt’s approach is further improved to avoid any numerical difficulty, i.e. overflow or underflow, in determining ip in cases BAgE iSVMi )(x is either too large or too small. otherwiseee Eife p ii i EE i E i 1 1 )1( 0)1( (24) Although there are significant differences between SVM and MLC, the probabilistic model above has uncovered the connection between these two classifiers....
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...In addition, in Lin et al [27] Platt’s approach is further improved to avoid any numerical difficulty, i....
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767 citations