登录
首页 » matlab » 机器学习matlab实现

机器学习matlab实现

于 2020-07-08 发布
0 168
下载积分: 1 下载次数: 6

代码说明:

说明:  使用matlab进行机器学习,内部有各种模式的识别算法,可详细参考(Using MATLAB for machine learning, there are various pattern recognition algorithms inside, which can be referred to in detail)

文件列表:

ml-in-action-master, 0 , 2019-05-20
ml-in-action-master\.gitignore, 449 , 2019-05-20
ml-in-action-master\66d5be0a46c202c4.jpg, 115961 , 2019-05-20
ml-in-action-master\LICENSE, 1063 , 2019-05-20
ml-in-action-master\README.md, 1747 , 2019-05-20
ml-in-action-master\chapter10, 0 , 2019-05-20
ml-in-action-master\chapter10\ANN_Mat.m, 589 , 2019-05-20
ml-in-action-master\chapter11, 0 , 2019-05-20
ml-in-action-master\chapter11\Adaboost_Mat.m, 747 , 2019-05-20
ml-in-action-master\chapter12, 0 , 2019-05-20
ml-in-action-master\chapter12\Kmeans_Mat.m, 598 , 2019-05-20
ml-in-action-master\chapter13, 0 , 2019-05-20
ml-in-action-master\chapter13\EM.m, 3817 , 2019-05-20
ml-in-action-master\chapter13\gaussPDF.m, 2013 , 2019-05-20
ml-in-action-master\chapter13\plotGMM.m, 2658 , 2019-05-20
ml-in-action-master\chapter13\plot_em.m, 327 , 2019-05-20
ml-in-action-master\chapter14, 0 , 2019-05-20
ml-in-action-master\chapter14\Kcenter_Mat.m, 600 , 2019-05-20
ml-in-action-master\chapter14\apriori_gen.m, 491 , 2019-05-20
ml-in-action-master\chapter15, 0 , 2019-05-20
ml-in-action-master\chapter15\Apriori_App_Self.m, 156 , 2019-05-20
ml-in-action-master\chapter15\apriori.m, 389 , 2019-05-20
ml-in-action-master\chapter15\apriori_gen.m, 504 , 2019-05-20
ml-in-action-master\chapter15\get_k_itemset.m, 500 , 2019-05-20
ml-in-action-master\chapter15\init.m, 252 , 2019-05-20
ml-in-action-master\chapter15\isExit.m, 343 , 2019-05-20
ml-in-action-master\chapter16, 0 , 2019-05-20
ml-in-action-master\chapter16\fitgmm.m, 2225 , 2019-05-20
ml-in-action-master\chapter16\gmm.m, 10889 , 2019-05-20
ml-in-action-master\chapter16\gmmcluster.m, 3717 , 2019-05-20
ml-in-action-master\chapter17, 0 , 2019-05-20
ml-in-action-master\chapter17\calDistance.m, 436 , 2019-05-20
ml-in-action-master\chapter17\dbscan.m, 3781 , 2019-05-20
ml-in-action-master\chapter17\demo_dbscan.m, 275 , 2019-05-20
ml-in-action-master\chapter17\epsilon.m, 426 , 2019-05-20
ml-in-action-master\chapter18, 0 , 2019-05-20
ml-in-action-master\chapter18\car_prob.m, 1658 , 2019-05-20
ml-in-action-master\chapter18\cmpt_P_and_R.m, 1754 , 2019-05-20
ml-in-action-master\chapter18\jcr_policy_evaluation.m, 1421 , 2019-05-20
ml-in-action-master\chapter18\jcr_policy_improvement.m, 1559 , 2019-05-20
ml-in-action-master\chapter18\jcr_rhs_state_value_bellman.m, 625 , 2019-05-20
ml-in-action-master\chapter19, 0 , 2019-05-20
ml-in-action-master\chapter19\Q_update.m, 1592 , 2019-05-20
ml-in-action-master\chapter19\SARSA_CW.m, 4799 , 2019-05-20
ml-in-action-master\chapter19\learn_cw.m, 9468 , 2019-05-20
ml-in-action-master\chapter19\plot_cw_policy.m, 1681 , 2019-05-20
ml-in-action-master\chapter19\q_learn.m, 4609 , 2019-05-20
ml-in-action-master\chapter19\script_cw.m, 3184 , 2019-05-20
ml-in-action-master\chapter19\transition.m, 1105 , 2019-05-20
ml-in-action-master\chapter2, 0 , 2019-05-20
ml-in-action-master\chapter2\Com_Exm.m, 1350 , 2019-05-20
ml-in-action-master\chapter2\For_if.m, 203 , 2019-05-20
ml-in-action-master\chapter2\For_switch.m, 409 , 2019-05-20
ml-in-action-master\chapter2\Mesh_Exm.m, 279 , 2019-05-20
ml-in-action-master\chapter2\Plot_Exm.m, 366 , 2019-05-20
ml-in-action-master\chapter2\Surf_Exm.m, 277 , 2019-05-20
ml-in-action-master\chapter2\Three_add.m, 74 , 2019-05-20
ml-in-action-master\chapter2\Three_ass_add.m, 106 , 2019-05-20
ml-in-action-master\chapter2\While_if.m, 252 , 2019-05-20
ml-in-action-master\chapter2\csvdata.csv, 23 , 2019-05-20
ml-in-action-master\chapter2\matdata.mat, 183 , 2019-05-20
ml-in-action-master\chapter2\txtdata.txt, 23 , 2019-05-20
ml-in-action-master\chapter2\xlsdata.xls, 25088 , 2019-05-20
ml-in-action-master\chapter2\xlsxdata.xlsx, 25088 , 2019-05-20
ml-in-action-master\chapter4, 0 , 2019-05-20
ml-in-action-master\chapter4\KNNA_Self.m, 2525 , 2019-05-20
ml-in-action-master\chapter4\KNN_Mat.m, 682 , 2019-05-20
ml-in-action-master\chapter5, 0 , 2019-05-20
ml-in-action-master\chapter5\Dectree_Mat.m, 269 , 2019-05-20
ml-in-action-master\chapter6, 0 , 2019-05-20
ml-in-action-master\chapter6\SVM_Mat.m, 513 , 2019-05-20
ml-in-action-master\chapter7, 0 , 2019-05-20
ml-in-action-master\chapter7\NB_Mat.m, 258 , 2019-05-20
ml-in-action-master\chapter8, 0 , 2019-05-20
ml-in-action-master\chapter8\LineRe_Mat.m, 992 , 2019-05-20
ml-in-action-master\chapter9, 0 , 2019-05-20
ml-in-action-master\chapter9\glm.m, 8370 , 2019-05-20
ml-in-action-master\chapter9\gradDescent.m, 396 , 2019-05-20
ml-in-action-master\chapter9\sigmoid.m, 121 , 2019-05-20
ml-in-action-master\frontpage.png, 224724 , 2019-05-20

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • 此游戏是基于 hge 1.81 写的,是一个简单的打砖块游戏
    此游戏是基于 hge 1.81 写的,是一个简单的打砖块游戏-This game is based on HGE 1.81SDK. it s an easy BLCOK THROUGHT game
    2022-09-23 05:30:04下载
    积分:1
  • jzb (2)
    说明:  水声 简正波计算海洋声场程序 自编 各个参数同书上理论(Underwater acoustic channel Normal wave calculation ocean sound field program)
    2021-01-08 20:32:06下载
    积分:1
  • walkingpete小程序!
    一个walkingpete的小程序-walkingpete a small procedure!
    2022-07-06 12:11:14下载
    积分:1
  • rpsmooth
    粗糙惩罚平滑算法的matlab实现,很详细,亲测有效(Roughness Penalty Smoothing)
    2021-02-01 16:40:00下载
    积分:1
  • 串口测试,基于VC++,多线程编程,可同时测量四个串口
    串口测试,基于VC++,多线程编程,可同时测量四个串口-Serial test, based on VC++, multi-threaded programming, which can measure four serial ports
    2022-03-20 08:48:17下载
    积分:1
  • 粒子群算法试算
    粒子群算法,也称粒子群优化算法(Particle Swarm Optimization),缩写为 PSO, 是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种,和模拟退火算法相似,它也是从随机解出发,通过迭代寻找最优解,它也是通过适应度来评价解的品质,但它比遗传算法规则更为简单,它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作,它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视,并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。(Particle swarm optimization (PSO), also called particle swarm optimization (Particle Swarm Optimization), is abbreviated as PSO, which is a new evolutionary algorithm (Evolutionary Algorithm EA) developed in recent years. PSO algorithm is a kind of evolutionary algorithm. It is similar to simulated annealing algorithm. It also starts from the random solution and finds the optimal solution by iteration. It also evaluates the quality of the solution through fitness, but it is simpler than the genetic algorithm rule. It does not have the crossover (Crossover) and the Mutation operation of genetic algorithm. Search for global optimum. This algorithm has attracted the attention of the academic community for its advantages of easy realization, high accuracy and fast convergence, and has shown its superiority in solving practical problems. Particle swarm optimization (PSO) is a parallel algorithm.)
    2018-12-25 14:28:52下载
    积分:1
  • 雷傲极酷超级论坛LeoBBS X 040601 简体正式版
    雷傲极酷超级论坛LeoBBS X 040601 简体正式版-mine very proud Super Cool Forum LeoBBS X 040601 English version
    2022-12-19 12:05:04下载
    积分:1
  • 温度植被干旱指数计算
    说明:  采用IDL语言,可以用来计算植被干旱指数,输入影像即可(Using IDL language, it can be used to calculate vegetation drought index, just input image)
    2021-01-21 23:33:24下载
    积分:1
  • AFWA-dim30
    隐含层节点30,烟花优化算法,包含特征选取、数理统计、平均值等(evaluate.m;evaluatearray.m;sparksnumfireworkamplitude-cal.m)
    2020-06-17 14:00:01下载
    积分:1
  • LCD Driver 51 MCU
    tft320x240液晶显示驱动 并行接口 51单片机驱动程序-LCD Driver 51 MCU
    2022-01-22 01:26:50下载
    积分:1
  • 696518资源总数
  • 105559会员总数
  • 1今日下载