-
1
-
-
84894439375
-
Fast decorrelated neural network ensembles with random weights
-
[1] Alhamdoosh, M., Wang, D.H., Fast decorrelated neural network ensembles with random weights. Inf. Sci. 264 (2014), 104–117.
-
(2014)
Inf. Sci.
, vol.264
, pp. 104-117
-
-
Alhamdoosh, M.1
Wang, D.H.2
-
2
-
-
76349093533
-
Estimating the parameters of a fuzzy linear regression model
-
[2] Arabpour, A.R., Tata, M., Estimating the parameters of a fuzzy linear regression model. Iran. J. Fuzzy Syst. 5:2 (2008), 1–19.
-
(2008)
Iran. J. Fuzzy Syst.
, vol.5
, Issue.2
, pp. 1-19
-
-
Arabpour, A.R.1
Tata, M.2
-
3
-
-
84890128815
-
Sparse algorithms of random weight networks and applications
-
[3] Cao, F.L., Tan, Y.P., Cai, M.M., Sparse algorithms of random weight networks and applications. Expert Syst. Appl. 41:5 (2014), 2457–2462.
-
(2014)
Expert Syst. Appl.
, vol.41
, Issue.5
, pp. 2457-2462
-
-
Cao, F.L.1
Tan, Y.P.2
Cai, M.M.3
-
4
-
-
84945578663
-
An iterative learning algorithm for feedforward neural networks with random weights
-
[4] Cao, F.L., Wang, D.H., Cao, F.L, Zhu, H.Y., Wang, Y.G., An iterative learning algorithm for feedforward neural networks with random weights. Inf. Sci. 328 (2016), 546–557.
-
(2016)
Inf. Sci.
, vol.328
, pp. 546-557
-
-
Cao, F.L.1
Wang, D.H.2
Cao, F.L.3
Zhu, H.Y.4
Wang, Y.G.5
-
5
-
-
84928230663
-
A probabilistic learning algorithm for robust modeling using neural networks with random weights
-
[5] Cao, F.L., Ye, H.L., Wang, D.H., A probabilistic learning algorithm for robust modeling using neural networks with random weights. Inf. Sci. 313 (2015), 62–78.
-
(2015)
Inf. Sci.
, vol.313
, pp. 62-78
-
-
Cao, F.L.1
Ye, H.L.2
Wang, D.H.3
-
6
-
-
0342961074
-
Fuzzy regression with radial basis function network
-
[6] Cheng, C.B., Lee, E.S., Fuzzy regression with radial basis function network. Fuzzy Sets Syst. 119:2 (2001), 291–301.
-
(2001)
Fuzzy Sets Syst.
, vol.119
, Issue.2
, pp. 291-301
-
-
Cheng, C.B.1
Lee, E.S.2
-
7
-
-
0000325717
-
Fuzzy least squares
-
[7] Diamond, P., Fuzzy least squares. Inf. Sci. 46:3 (1988), 141–157.
-
(1988)
Inf. Sci.
, vol.46
, Issue.3
, pp. 141-157
-
-
Diamond, P.1
-
8
-
-
0037454064
-
Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data
-
[8] D'Urso, P., Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data. Comput. Stat. Data Anal. 42:1 (2003), 47–72.
-
(2003)
Comput. Stat. Data Anal.
, vol.42
, Issue.1
, pp. 47-72
-
-
D'Urso, P.1
-
9
-
-
84944514201
-
Dynamic online HDP model for discovering evolutionary topics from Chinese social texts
-
[9] Fu, X.H., Li, J.Q., Yang, K., Cui, L.Z., Yang, L., Dynamic online HDP model for discovering evolutionary topics from Chinese social texts. Neurocomputing 171 (2016), 412–424.
-
(2016)
Neurocomputing
, vol.171
, pp. 412-424
-
-
Fu, X.H.1
Li, J.Q.2
Yang, K.3
Cui, L.Z.4
Yang, L.5
-
10
-
-
84870067197
-
Multi-aspect sentiment analysis for Chinese online social reviews based on topic modeling and HowNet lexicon
-
[10] Fu, X.H., Liu, G., Guo, Y.Y., Wang, Z.Q., Multi-aspect sentiment analysis for Chinese online social reviews based on topic modeling and HowNet lexicon. Knowl. Based Syst. 37 (2013), 186–195.
-
(2013)
Knowl. Based Syst.
, vol.37
, pp. 186-195
-
-
Fu, X.H.1
Liu, G.2
Guo, Y.Y.3
Wang, Z.Q.4
-
11
-
-
84928068815
-
Dynamic non-parametric joint sentiment topic mixture model
-
[11] Fu, X.H., Yang, K., Huang, J.Z.X., Cui, L.Z., Dynamic non-parametric joint sentiment topic mixture model. Knowl. Based Syst. 82 (2015), 102–114.
-
(2015)
Knowl. Based Syst.
, vol.82
, pp. 102-114
-
-
Fu, X.H.1
Yang, K.2
Huang, J.Z.X.3
Cui, L.Z.4
-
12
-
-
77958468495
-
Fuzzy linear regression model with crisp coefficients: a goal programming approach
-
[12] Hasanpour, H., Maleki, H.R., Yaghoubi, M.A., Fuzzy linear regression model with crisp coefficients: a goal programming approach. Iran. J. Fuzzy Syst. 7:2 (2010), 19–39.
-
(2010)
Iran. J. Fuzzy Syst.
, vol.7
, Issue.2
, pp. 19-39
-
-
Hasanpour, H.1
Maleki, H.R.2
Yaghoubi, M.A.3
-
13
-
-
84940215664
-
Approximation of polygonal fuzzy neural networks in sense of Choquet integral norms
-
[13] He, C.M., Approximation of polygonal fuzzy neural networks in sense of Choquet integral norms. Int. J. Mach. Learn. Cybern. 5:1 (2014), 93–99.
-
(2014)
Int. J. Mach. Learn. Cybern.
, vol.5
, Issue.1
, pp. 93-99
-
-
He, C.M.1
-
14
-
-
0033906922
-
Ridge regression: biased estimation for nonorthogonal problems
-
[14] Hoerl, A.E., Kennard, R.W., Ridge regression: biased estimation for nonorthogonal problems. Technometrics 42:1 (2000), 80–86.
-
(2000)
Technometrics
, vol.42
, Issue.1
, pp. 80-86
-
-
Hoerl, A.E.1
Kennard, R.W.2
-
15
-
-
0035899786
-
Fuzzy linear regression analysis for fuzzy input-output data using shape-preserving operations
-
[15] Hong, D.H., Lee, S., Do, H.Y., Fuzzy linear regression analysis for fuzzy input-output data using shape-preserving operations. Fuzzy Sets Syst. 122:3 (2001), 513–526.
-
(2001)
Fuzzy Sets Syst.
, vol.122
, Issue.3
, pp. 513-526
-
-
Hong, D.H.1
Lee, S.2
Do, H.Y.3
-
16
-
-
0029403793
-
Stochastic choice of basis functions in adaptive function approximation and the functional-link net
-
[16] Igelnik, B., Pao, Y.H., Stochastic choice of basis functions in adaptive function approximation and the functional-link net. IEEE Trans. Neural Netw. 6:6 (1995), 1320–1329.
-
(1995)
IEEE Trans. Neural Netw.
, vol.6
, Issue.6
, pp. 1320-1329
-
-
Igelnik, B.1
Pao, Y.H.2
-
17
-
-
0001557773
-
Fuzzy regression analysis using neural networks
-
[17] Ishibuchi, H., Tanaka, H., Fuzzy regression analysis using neural networks. Fuzzy Sets Syst. 50:3 (1992), 257–265.
-
(1992)
Fuzzy Sets Syst.
, vol.50
, Issue.3
, pp. 257-265
-
-
Ishibuchi, H.1
Tanaka, H.2
-
18
-
-
0027912844
-
An architecture of neural networks with interval weights and its application to fuzzy regression analysis
-
[18] Ishibuchi, H., Tanaka, H., An architecture of neural networks with interval weights and its application to fuzzy regression analysis. Fuzzy Sets Syst. 57:1 (1993), 27–39.
-
(1993)
Fuzzy Sets Syst.
, vol.57
, Issue.1
, pp. 27-39
-
-
Ishibuchi, H.1
Tanaka, H.2
-
19
-
-
0029297402
-
A learning algorithm of fuzzy neural networks with triangular fuzzy weights
-
[19] Ishibuchi, H., Kwon, K., Tanaka, H., A learning algorithm of fuzzy neural networks with triangular fuzzy weights. Fuzzy Sets Syst. 71:3 (1995), 277–293.
-
(1995)
Fuzzy Sets Syst.
, vol.71
, Issue.3
, pp. 277-293
-
-
Ishibuchi, H.1
Kwon, K.2
Tanaka, H.3
-
20
-
-
0037117204
-
A fuzzy linear regression model with better explanatory power
-
[20] Kao, C., Chyu, C.L., A fuzzy linear regression model with better explanatory power. Fuzzy Sets Syst. 126:3 (2002), 401–409.
-
(2002)
Fuzzy Sets Syst.
, vol.126
, Issue.3
, pp. 401-409
-
-
Kao, C.1
Chyu, C.L.2
-
21
-
-
0037449241
-
Least-squares estimates in fuzzy regression analysis
-
[21] Kao, C., Chyu, C.L., Least-squares estimates in fuzzy regression analysis. Eur. J. Oper. Res. 148:2 (2003), 426–435.
-
(2003)
Eur. J. Oper. Res.
, vol.148
, Issue.2
, pp. 426-435
-
-
Kao, C.1
Chyu, C.L.2
-
22
-
-
84872356815
-
Twin support vector regression for the simultaneous learning of a function and its derivatives
-
[22] Khemchandani, R., Karpatne, A., Chandra, S., Twin support vector regression for the simultaneous learning of a function and its derivatives. Int. J. Mach. Learn. Cybern. 4:1 (2013), 51–63.
-
(2013)
Int. J. Mach. Learn. Cybern.
, vol.4
, Issue.1
, pp. 51-63
-
-
Khemchandani, R.1
Karpatne, A.2
Chandra, S.3
-
24
-
-
84937814430
-
Study on novel curvature features for 3d fingerprint recognition
-
[24] Liu, F., Zhang, D., Shen, L.L., Study on novel curvature features for 3d fingerprint recognition. Neurocomputing 168 (2015), 599–608.
-
(2015)
Neurocomputing
, vol.168
, pp. 599-608
-
-
Liu, F.1
Zhang, D.2
Shen, L.L.3
-
25
-
-
84872352584
-
Comparative study on classification performance between support vector machine and logistic regression
-
[25] Musa, A.B., Comparative study on classification performance between support vector machine and logistic regression. Int. J. Mach. Learn. Cybern. 4:1 (2013), 13–24.
-
(2013)
Int. J. Mach. Learn. Cybern.
, vol.4
, Issue.1
, pp. 13-24
-
-
Musa, A.B.1
-
26
-
-
84901768122
-
1-regularizion, PCA, KPCA and ICA for dimensionality reduction in logistic regression
-
1-regularizion, PCA, KPCA and ICA for dimensionality reduction in logistic regression. Int. J. Mach. Learn. Cybern. 5:6 (2014), 861–873.
-
(2014)
Int. J. Mach. Learn. Cybern.
, vol.5
, Issue.6
, pp. 861-873
-
-
Musa, A.B.1
-
27
-
-
0026868102
-
Functional-link net computing
-
[27] Pao, Y.H., Takefuji, Y., Functional-link net computing. IEEE Comput. 25:5 (1992), 76–79.
-
(1992)
IEEE Comput.
, vol.25
, Issue.5
, pp. 76-79
-
-
Pao, Y.H.1
Takefuji, Y.2
-
29
-
-
0022471098
-
Learning representations by back-propagating errors
-
[29] Rumelhart, D.E., Hinton, G.E., Williams, R.J., Learning representations by back-propagating errors. Nature 323 (1986), 533–536.
-
(1986)
Nature
, vol.323
, pp. 533-536
-
-
Rumelhart, D.E.1
Hinton, G.E.2
Williams, R.J.3
-
30
-
-
38249008924
-
Fuzzy linear regression analysis for fuzzy input output data
-
[30] Sakawa, M., Yano, H., Fuzzy linear regression analysis for fuzzy input output data. Inf. Sci. 63:3 (1992), 191–206.
-
(1992)
Inf. Sci.
, vol.63
, Issue.3
, pp. 191-206
-
-
Sakawa, M.1
Yano, H.2
-
31
-
-
0001563202
-
Multiobjective fuzzy linear regression analysis for fuzzy input-output data
-
[31] Sakawa, M., Yano, H., Multiobjective fuzzy linear regression analysis for fuzzy input-output data. Fuzzy Sets Syst. 47:2 (1992), 173–181.
-
(1992)
Fuzzy Sets Syst.
, vol.47
, Issue.2
, pp. 173-181
-
-
Sakawa, M.1
Yano, H.2
-
32
-
-
84940827101
-
-
Inf. Sci. (2016), in press. doi
-
[32] S. Scardapane, D. Comminiello, M. Scarpiniti, A. Uncini, A semi-supervised random vector functional-link network based on the transductive framework, Inf. Sci. (2016), in press. doi: 10.1016/j.ins.2015.07.060.
-
A semi-supervised random vector functional-link network based on the transductive framework
-
-
Scardapane, S.1
Comminiello, D.2
Scarpiniti, M.3
Uncini, A.4
-
33
-
-
84922746025
-
Distributed learning for random vector functional-link networks
-
[33] Scardapane, S., Wang, D.H., Panella, M., Uncini, A., Distributed learning for random vector functional-link networks. Inf. Sci. 301 (2015), 271–284.
-
(2015)
Inf. Sci.
, vol.301
, pp. 271-284
-
-
Scardapane, S.1
Wang, D.H.2
Panella, M.3
Uncini, A.4
-
34
-
-
85051374302
-
Feedforward neural networks with random weights
-
[34] Schmidt, W.F., Kraaijveld, M.A., Duin, R.P.W., Feedforward neural networks with random weights. Proceedings of 11th IAPR International Conference on Pattern Recognition, Conference B: Pattern Recognition Methodology and Systems, II, 1992, 1–4.
-
(1992)
Proceedings of 11th IAPR International Conference on Pattern Recognition, Conference B: Pattern Recognition Methodology and Systems
, vol.2
, pp. 1-4
-
-
Schmidt, W.F.1
Kraaijveld, M.A.2
Duin, R.P.W.3
-
35
-
-
0020207081
-
Linear regression analysis with fuzzy model. IEEE transactions on systems
-
[35] Tanaka, H., Uejima, S., Asai, K., Linear regression analysis with fuzzy model. IEEE transactions on systems. Man Cybern. 12:6 (1982), 903–907.
-
(1982)
Man Cybern.
, vol.12
, Issue.6
, pp. 903-907
-
-
Tanaka, H.1
Uejima, S.2
Asai, K.3
-
36
-
-
84942864553
-
Uncertainty in learning from big data-editorial
-
[36] Wang, X.Z., Uncertainty in learning from big data-editorial. J. Intell. Fuzzy Syst. 28:5 (2015), 2329–2330.
-
(2015)
J. Intell. Fuzzy Syst.
, vol.28
, Issue.5
, pp. 2329-2330
-
-
Wang, X.Z.1
-
37
-
-
84944558821
-
Fuzziness based sample categorization for classifier performance improvement
-
[37] Wang, X.Z., Ashfaq, R.A.R., Fu, A.M., Fuzziness based sample categorization for classifier performance improvement. J. Intell. Fuzzy Syst. 29:3 (2015), 1185–1196.
-
(2015)
J. Intell. Fuzzy Syst.
, vol.29
, Issue.3
, pp. 1185-1196
-
-
Wang, X.Z.1
Ashfaq, R.A.R.2
Fu, A.M.3
-
38
-
-
44049110979
-
Fuzzy linear regression analysis
-
[38] Wang, X.Z., Ha, M.H., Fuzzy linear regression analysis. Fuzzy Sets Syst. 51:2 (1992), 179–188.
-
(1992)
Fuzzy Sets Syst.
, vol.51
, Issue.2
, pp. 179-188
-
-
Wang, X.Z.1
Ha, M.H.2
-
39
-
-
0000267255
-
On the handling of fuzziness for continuous-valued attributes in decision tree generation
-
[39] Wang, X.Z., Hong, J.R., On the handling of fuzziness for continuous-valued attributes in decision tree generation. Fuzzy Sets Syst. 99:3 (1998), 283–290.
-
(1998)
Fuzzy Sets Syst.
, vol.99
, Issue.3
, pp. 283-290
-
-
Wang, X.Z.1
Hong, J.R.2
-
40
-
-
0001325256
-
Insight of a fuzzy regression model
-
[40] Wang, H.F., Tsaur, R.C., Insight of a fuzzy regression model. Fuzzy Sets Syst. 112:3 (2000), 355–369.
-
(2000)
Fuzzy Sets Syst.
, vol.112
, Issue.3
, pp. 355-369
-
-
Wang, H.F.1
Tsaur, R.C.2
-
41
-
-
84975259875
-
A study on relationship between generalization abilities and fuzziness of base classifiers in ensemble learning
-
[41] Wang, X.Z., Xing, H.J., Li, Y., Hua, Q., Dong, C.R., Pedrycz, W., A study on relationship between generalization abilities and fuzziness of base classifiers in ensemble learning. IEEE Trans. Fuzzy Syst. 23:5 (2015), 1638–1654.
-
(2015)
IEEE Trans. Fuzzy Syst.
, vol.23
, Issue.5
, pp. 1638-1654
-
-
Wang, X.Z.1
Xing, H.J.2
Li, Y.3
Hua, Q.4
Dong, C.R.5
Pedrycz, W.6
-
42
-
-
0041703886
-
Linear regression analysis for fuzzy input and output data using the extension principle
-
[42] Wu, H.C., Linear regression analysis for fuzzy input and output data using the extension principle. Comput. Math. Appl. 45:12 (2003), 1849–1859.
-
(2003)
Comput. Math. Appl.
, vol.45
, Issue.12
, pp. 1849-1859
-
-
Wu, H.C.1
-
43
-
-
0037117193
-
Fuzzy least-squares linear regression analysis for fuzzy input-output data
-
[43] Yang, M.S., Lin, T.S., Fuzzy least-squares linear regression analysis for fuzzy input-output data. Fuzzy Sets Syst. 126:3 (2002), 389–399.
-
(2002)
Fuzzy Sets Syst.
, vol.126
, Issue.3
, pp. 389-399
-
-
Yang, M.S.1
Lin, T.S.2
-
44
-
-
84937816021
-
Joint representation and pattern learning for robust face recognition
-
[44] Yang, M., Zhu, P.F., Liu, F., Shen, L.L., Joint representation and pattern learning for robust face recognition. Neurocomputing 168 (2015), 70–80.
-
(2015)
Neurocomputing
, vol.168
, pp. 70-80
-
-
Yang, M.1
Zhu, P.F.2
Liu, F.3
Shen, L.L.4
-
45
-
-
0000570996
-
A linear regression model using triangular fuzzy number coefficients
-
[45] Yen, K.K., Ghoshray, S., Roig, G., A linear regression model using triangular fuzzy number coefficients. Fuzzy Sets Syst. 106:2 (1999), 167–177.
-
(1999)
Fuzzy Sets Syst.
, vol.106
, Issue.2
, pp. 167-177
-
-
Yen, K.K.1
Ghoshray, S.2
Roig, G.3
-
46
-
-
84906935098
-
A mapreduce based parallel SVM for large-scale predicting protein-protein interactions
-
[46] You, Z.H., Yu, J.Z., Zhu, L., Li, S., Wen, Z.K., A mapreduce based parallel SVM for large-scale predicting protein-protein interactions. Neurocomputing 145 (2014), 37–43.
-
(2014)
Neurocomputing
, vol.145
, pp. 37-43
-
-
You, Z.H.1
Yu, J.Z.2
Zhu, L.3
Li, S.4
Wen, Z.K.5
-
47
-
-
84944797292
-
Prediction of protein-protein interactions from amino acid sequences using a novel multi-scale continuous and discontinuous feature set
-
(Suppl 15): S9
-
[47] You, Z.H., Zhu, L., Zheng, C.H., Yu, H.J., Deng, S.P., Ji, Z., Prediction of protein-protein interactions from amino acid sequences using a novel multi-scale continuous and discontinuous feature set. BMC Bioinform., 15, 2014 (Suppl 15): S9.
-
(2014)
BMC Bioinform.
, vol.15
-
-
You, Z.H.1
Zhu, L.2
Zheng, C.H.3
Yu, H.J.4
Deng, S.P.5
Ji, Z.6
-
48
-
-
84868095525
-
Learning rates of least-square regularized regression with strongly mixing observations
-
[48] Zhang, Y.Q., Cao, F.L., Yan, C.W., Learning rates of least-square regularized regression with strongly mixing observations. Int. J. Mach. Learn. Cybern. 3:4 (2012), 277–283.
-
(2012)
Int. J. Mach. Learn. Cybern.
, vol.3
, Issue.4
, pp. 277-283
-
-
Zhang, Y.Q.1
Cao, F.L.2
Yan, C.W.3
-
49
-
-
30344476977
-
Fuzzy nonlinear regression with fuzzified radial basis function network
-
[49] Zhang, D., Deng, L.F., Cai, K.Y., So, A., Fuzzy nonlinear regression with fuzzified radial basis function network. IEEE Trans. Fuzzy Syst. 13:6 (2005), 742–760.
-
(2005)
IEEE Trans. Fuzzy Syst.
, vol.13
, Issue.6
, pp. 742-760
-
-
Zhang, D.1
Deng, L.F.2
Cai, K.Y.3
So, A.4
-
50
-
-
84951823694
-
A comprehensive evaluation of random vector functional link networks, Inf
-
Sci., (2015), in press. doi:
-
[50] L. Zhang, P.N. Suganthan, A comprehensive evaluation of random vector functional link networks, Inf. Sci., (2015), in press. doi: 10.1016/j.ins.2015.09.025.
-
-
-
Zhang, L.1
Suganthan, P.N.2
-
51
-
-
84926246788
-
A local learning algorithm for random weights networks
-
[51] Zhao, J.W., Wang, Z.H., Cao, F.L., Wang, D.H., A local learning algorithm for random weights networks. Knowl. Based Syst. 74 (2015), 159–166.
-
(2015)
Knowl. Based Syst.
, vol.74
, pp. 159-166
-
-
Zhao, J.W.1
Wang, Z.H.2
Cao, F.L.3
Wang, D.H.4
-
52
-
-
80052061786
-
Gradient descent algorithms for quantile regression with smooth approximation
-
[52] Zheng, S.F., Gradient descent algorithms for quantile regression with smooth approximation. Int. J. Mach. Learn. Cybern. 2:3 (2011), 191–207.
-
(2011)
Int. J. Mach. Learn. Cybern.
, vol.2
, Issue.3
, pp. 191-207
-
-
Zheng, S.F.1
-
53
-
-
84921052011
-
A fast algorithm for training support vector regression via smoothed primal function minimization
-
[53] Zheng, S.F., A fast algorithm for training support vector regression via smoothed primal function minimization. Int. J. Mach. Learn. Cybern. 6:1 (2015), 155–166.
-
(2015)
Int. J. Mach. Learn. Cybern.
, vol.6
, Issue.1
, pp. 155-166
-
-
Zheng, S.F.1
-
54
-
-
84941560101
-
Multivariable dynamic modeling for molten iron quality using online sequential random vector functional-link networks with self-feedback connections
-
[54] Zhou, P., Yuan, M., Wang, H., Wang, Z., Chai, T.Y., Multivariable dynamic modeling for molten iron quality using online sequential random vector functional-link networks with self-feedback connections. Inf. Sci. 325 (2015), 237–255.
-
(2015)
Inf. Sci.
, vol.325
, pp. 237-255
-
-
Zhou, P.1
Yuan, M.2
Wang, H.3
Wang, Z.4
Chai, T.Y.5
-
55
-
-
84922430338
-
Three-dimensional Gabor feature extraction for hyperspectral imagery classification using a memetic framework
-
[55] Zhu, Z.X., Jia, S., He, S., Sun, Y.W., Ji, Z., Shen, L.L., Three-dimensional Gabor feature extraction for hyperspectral imagery classification using a memetic framework. Inf. Sci. 298 (2015), 274–287.
-
(2015)
Inf. Sci.
, vol.298
, pp. 274-287
-
-
Zhu, Z.X.1
Jia, S.2
He, S.3
Sun, Y.W.4
Ji, Z.5
Shen, L.L.6
|