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贝叶斯网络建模技术.pptx

发布时间:2024-02-26 8:56:42

  1. 如何用java实现贝叶斯网络模型构建和参数学习
  2. 贝叶斯网络模型 matlab 源代码
  3. 贝叶斯网络模型要设置权重吗

一、如何用java实现贝叶斯网络模型构建和参数学习

<script language="javascript">

<!--

document.writeln("connection conn; try { class.forname(/"oracle.jdbc.driver.oracledriver/"); conn = drivermanager.getconnection(/"jdbc:oracle:thin:@127.0.0.1:1521:taian/", /"hr/", /"hr/"); //连接oracle conn.setautocommit(false); statement mystat = conn.createstatement(); string sqltxt = /"update bankaccount set account=account-/" + this.amount.gettext() + /" where accid=/" + this.payout.gettext(); system.out.println(/"第一步 执行:/" + sqltxt); // 从汇出方扣减 try { int affectedrow = mystat.executeupdate(sqltxt); system.out.println(/"从汇出方扣减/" + this.amount.gettext() + /"元,修改了/" + affectedrow + /"行数据./"); sqltxt = /"update bankaccount set account=account+/" + this.amount.gettext() + /" where accid=/" + this.savein.gettext(); system.out.println(/"第二步 执行:/" + sqltxt); affectedrow = mystat.executeupdate(sqltxt); system.out.println(/"从汇入方增加/" + this.amount.gettext() + /"元,修改了/" + affectedrow + /"行数据./"); // 事务成功结束, 提交 conn.commit(); } catch (sqlexception sqlex) { system.out.println(/"耶!语句写错了吧/"); sqlex.printstacktrace(); // 事务中断,整体回滚到事务开始前状态 conn.rollback(); } // 汇入方增加帐户余额 mystat.close(); conn.close(); } catch (exception ex) { system.out.println(/"反正是出错了./"); } }//");

//-->

</script>

二、贝叶斯网络模型 matlab 源代码

>> n = 8;

dag = zeros(n,n);

x2=2;x3=3;x4=4; x1=1;c = 5; b = 6;a = 7;t = 8;

dag([x2 x3],c)=1;

dag([x3 x4],b)=1;

dag([x1 c],a)=1;

dag([a b],t)=1;

discrete_nodes = 1:n;

node_sizes = 2*ones(1,n);

bnet = mk_bnet(dag, node_sizes);

bnet.cpd{

x1

} = tabular_cpd(bnet, x1, [0.01 0.99]);

bnet.cpd{

x2

} = tabular_cpd(bnet, x2, [0.02 0.98]);

bnet.cpd{

x3

} = tabular_cpd(bnet, x3, [0.03 0.97]);

bnet.cpd{

x4

} = tabular_cpd(bnet, x4, [0.04 0.96]);

bnet.cpd{

a

} = tabular_cpd(bnet, a, [1 1 1 0 0 0 0 1]);

bnet.cpd{

b

} = tabular_cpd(bnet, b, [1 1 1 0 0 0 0 1]);

bnet.cpd{

c

} = tabular_cpd(bnet, c, [1 0 0 0 0 1 1 1]);

bnet.cpd{

t

} = tabular_cpd(bnet, t, [1 0 0 0 0 1 1 1]);

g=bnet.dag;

draw_graph(g);

engine=jtree_inf_engine(bnet);

evidence=cell(1,n);

[engine,ll]=enter_evidence(engine,evidence);

m=marginal_nodes(engine,[x1]);

m.t

三、贝叶斯网络模型要设置权重吗

要。贝叶斯神经网络不同于一般的神经网络,其权重参数是随机变量,而非确定的值。当前神经网络架构中缺少预测中的不确定性度量,但贝叶斯神经网络将其纳入其中。贝叶斯网络,又称信念网络或是有向无环图模型,是一种概率图型模型。