行为分类算法

Posted 2020-11-27 caoke

根据两个用户的行为记录

[

[ 0, 1, 4, 9 ],
[ 8, 0, 7, 2 ]

]

，找出中间记录[4,0.5,5.5,5.5]，生成特征

[

[ 0, 1, 0, 1 ],
[ 1, 0, 1, 0 ]

]

求出特征出现概率

[1/2,1/2,1/2,1/2]

输入新的行为,更具中间记录，生成特征，更具特征概率，新的行为和旧的行为是一类的概率为贝叶斯联合概率

const execMathExpress=require(‘exec-mathexpress‘);
//贝叶斯计算公式
function execByes(gArr){
  const arr1=[]
  const arr2=[]
  const Obj={}
  for(let i=0;i<gArr.length;i++){
    arr1.push(‘P‘+i)
    arr2.push(‘(1-P‘+i+‘)‘)
    Obj[‘P‘+i]=gArr[i];
  }
  const str1=arr1.join(‘*‘);
  const str2=arr2.join(‘*‘);
  const str=str1+‘/(‘+str1+‘+‘+str2+‘)‘;
  return execMathExpress(str,Obj).toString();
}

class People {
  constructor(keys){
    this.keys=keys;
    this.data=[]
  }
  learn(item){
    this.data.push(item);
  }
  getFeature(item){
    const arr=[];
    const den=this.data.length;
    for(let i=0;i<this.keys.length;i++){
      let pNum=0;
      for(let j=0;j<den;j++){
        const d=this.data[j];
        if(item[i]>d[i]){
          pNum++;
        }
      }
      if(pNum>den/2){
        arr[i]=1;
      }else{
        arr[i]=0;
      }
    }
    return arr;
  }
  think(){

    const den=this.data.length;
    for(let i=0;i<this.keys.length;i++){
      let pNum=0;
      for(let j=0;j<den;j++){
        const d=this.data[j];
        if(item[i]>d[i]){
          pNum++;
        }
      }
      if(pNum>den/2){
        arr[i]=1;
      }else{
        arr[i]=0;
      }
    }
  }
  getOrder(item){
    const arr=this.getFeature(item,this.keys);
    console.log(arr)
    console.log(execByes(arr))
    return execByes(arr);
  }
}

const d=new People([‘show‘,‘click‘,‘a‘,‘time‘])
function randomArr(){
  const arr=[];
  for(let i=0;i<4;i++){
    const n=0|Math.random()*10;
    arr.push(n)
  }
    return arr
}
const rect=[ [ 0, 1, 4, 9 ],
  [ 8, 0, 7, 2 ],
  [ 9, 9, 1, 8 ],
  [ 1, 0, 6, 7 ],
  [ 1, 3, 7, 5 ],
  [ 5, 5, 0, 9 ],
  [ 7, 6, 0, 4 ],
  [ 5, 5, 2, 9 ],
  [ 6, 2, 9, 5 ],
  [ 3, 5, 3, 3 ] ];
for(let i=0;i<4;i++){
  rect.push(randomArr())
}
rect.forEach(function (item) {
  d.learn(item)
})

console.log(d)
d.getOrder(randomArr());
d.getOrder(randomArr());
d.getOrder(randomArr());
d.getOrder(randomArr());
d.getOrder(randomArr());
d.getOrder(randomArr());
d.getOrder(randomArr());