文件名称:HK
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HK算法思想很朴实,就是在最小均方误差准则下求得权矢量.
他相对于感知器算法的优点在于,他适用于线性可分和非线性可分得情况,对于线性可分的情况,给出最优权矢量,对于非线性可分得情况,能够判别出来,以退出迭代过程.(The idea of HK algorithm is very simple, which is to obtain the weight vector under the minimum mean square error criterion.
Compared with the perceptron algorithm, it is suitable for linear separable and non-linear separable cases. For linear separable cases, the optimal weight vector is given. For non-linear separable cases, it can be distinguished to exit the iteration process.)
他相对于感知器算法的优点在于,他适用于线性可分和非线性可分得情况,对于线性可分的情况,给出最优权矢量,对于非线性可分得情况,能够判别出来,以退出迭代过程.(The idea of HK algorithm is very simple, which is to obtain the weight vector under the minimum mean square error criterion.
Compared with the perceptron algorithm, it is suitable for linear separable and non-linear separable cases. For linear separable cases, the optimal weight vector is given. For non-linear separable cases, it can be distinguished to exit the iteration process.)
相关搜索: HK
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下载文件列表
文件名 | 大小 | 更新时间 |
---|---|---|
HK\DataSetUCI\banana_v.mat | 38512 | 2017-07-26 |
HK\DataSetUCI\banknote_authentication_v.mat | 34406 | 2017-05-29 |
HK\DataSetUCI\breast_cancer_wisconsin_v.mat | 2484 | 2017-05-29 |
HK\DataSetUCI\cardiotocography_v.mat | 74334 | 2017-07-26 |
HK\DataSetUCI\clean1_v.mat | 105743 | 2017-05-29 |
HK\DataSetUCI\cmc_v.mat | 5277 | 2017-05-29 |
HK\DataSetUCI\coil_20_v.mat | 1907586 | 2017-05-29 |
HK\DataSetUCI\connect4_v.mat | 226157 | 2017-07-26 |
HK\DataSetUCI\EEGEyeState_v.mat | 424141 | 2017-07-26 |
HK\DataSetUCI\Electricity_Board_v.mat | 717460 | 2017-07-26 |
HK\DataSetUCI\Gesture_Phase_Segmentation_v.mat | 1298692 | 2017-07-26 |
HK\DataSetUCI\Hill_Valley_v.mat | 870243 | 2017-05-29 |
HK\DataSetUCI\horse_colic_v.mat | 11180 | 2017-05-29 |
HK\DataSetUCI\House_vote_v.mat | 1666 | 2017-05-29 |
HK\DataSetUCI\ionosphere_v.mat | 56487 | 2017-05-29 |
HK\DataSetUCI\iris_v.mat | 1257 | 2017-05-29 |
HK\DataSetUCI\JAFFE_v.mat | 413096 | 2017-05-29 |
HK\DataSetUCI\letter_24x18_v.mat | 22973 | 2017-05-29 |
HK\DataSetUCI\letter_v.mat | 156018 | 2017-07-26 |
HK\DataSetUCI\magic_v.mat | 963875 | 2017-05-29 |
HK\DataSetUCI\marketing_v.mat | 40494 | 2017-05-29 |
HK\DataSetUCI\MINST58_v.mat | 2774504 | 2017-07-04 |
HK\DataSetUCI\Musk_v.mat | 109991 | 2017-05-29 |
HK\DataSetUCI\ORL_v.mat | 248191 | 2017-05-29 |
HK\DataSetUCI\penbased_v.mat | 133867 | 2017-05-29 |
HK\DataSetUCI\pima_indians_diabetes_v.mat | 14192 | 2017-05-29 |
HK\DataSetUCI\secom_v.mat | 2809112 | 2017-05-29 |
HK\DataSetUCI\segmentation_v.mat | 229163 | 2017-07-26 |
HK\DataSetUCI\semeion_v.mat | 55012 | 2017-05-29 |
HK\DataSetUCI\sonar_v.mat | 54458 | 2017-05-29 |
HK\DataSetUCI\spambase_v.mat | 226477 | 2017-07-26 |
HK\DataSetUCI\statlog_v.mat | 134607 | 2017-05-29 |
HK\DataSetUCI\transfusion_v.mat | 2853 | 2017-05-29 |
HK\DataSetUCI\twonorm_v.mat | 702557 | 2017-07-26 |
HK\DataSetUCI\WallFollowing24_v.mat | 335938 | 2017-07-26 |
HK\DataSetUCI\water_v.mat | 11506 | 2017-05-29 |
HK\DataSetUCI\waveform_v.mat | 249655 | 2017-05-29 |
HK\DataSetUCI\wdbc_v.mat | 94587 | 2017-05-29 |
HK\DataSetUCI\wine_v.mat | 6463 | 2017-05-29 |
HK\DataSetUCI\YaleB_v.mat | 2151022 | 2017-05-29 |
HK\DataSetUCI\Yale_v.mat | 162807 | 2017-05-29 |
HK\MHKS_UCI\getTrainAndTest.m | 396 | 2017-06-02 |
HK\MHKS_UCI\MHKS_Fun.m | 4868 | 2018-03-26 |
HK\MHKS_UCI\temp.m | 6193 | 2018-03-22 |
HK\MHKS_UCI\report | 0 | 2019-07-09 |
HK\DataSetUCI | 0 | 2019-07-09 |
HK\MHKS_UCI | 0 | 2019-07-09 |
HK | 0 | 2019-07-09 |