限制分类器输出在"0“和"1”之间
限制分类器输出在"0“和"1”之间
提问于 2020-11-11 01:46:42
我尝试使用朴素贝叶斯算法按对象值对数组进行分类，但我的结果是返回负值。我想让它返回0到1之间的值(代表百分比)这是我的分类器
class Bayes{
constructor(...categories) {
this.categories = {};
this.categoryCounts = {};
categories.forEach(category => {
this.categories[category] = {};
this.categoryCounts[category] = 0;
});
}
train(category, dataset) {
this.categoryCounts[category]++;
Object.keys(dataset).forEach(key => {
this.categories[category][key] = (this.categories[category][key] || 0) + dataset[key];
});
};
classify(dataset) {
let scores = {};
let trainingCount = Object.values(this.categoryCounts).reduce((a, b) => a + b );
Object.keys(this.categories).forEach(category => {
scores[category] = 0;
let categoryWords = this.categories[category];
let total = Object.values(categoryWords).reduce((a, b) => a + b );
Object.keys(dataset).forEach(function (key) {
let value = dataset[key];
let s = categoryWords[key] || 0.1;
let i = 0;
while(i<value){
scores[category] += Math.log(s / parseFloat(total));
i++;
}
});
let s = this.categoryCounts[category] || 0.1;
scores[category] += Math.log(s / trainingCount);
});
return scores;
};
};
var b = new Bayes('good', 'bad');
b.train('good', { dry: 1, wet: 0 });
b.train('bad', { dry: 0, wet: 1 });
b.train('good', { dry: 0, wet: 1, green: 1});
b.train('good', { dry: 1, wet: 0, green: 1});
console.log(b.classify({ dry: 0, wet: 1, green: 2}));下面是输出：
Object {
bad: -5.991464547107982,
good: -3.729701448634191
}我想以百分比形式返回结果，如下所示：
Object {
bad: 0.30,
good: 0.70
}提前感谢
回答 1
Stack Overflow用户
发布于 2020-11-12 00:15:43
我删除了scores[category] += Math.log(s / trainingCount);中的日志函数，
class Bayes{
constructor(...categories) {
this.categories = {};
this.categoryCounts = {};
categories.forEach(category => {
this.categories[category] = {};
this.categoryCounts[category] = 0;
});
}
train(category, dataset) {
this.categoryCounts[category]++;
Object.keys(dataset).forEach(key => {
this.categories[category][key] = (this.categories[category][key] || 0) + dataset[key];
});
};
classify(dataset) {
let scores = {};
let trainingCount = Object.values(this.categoryCounts).reduce((a, b) => a + b );
Object.keys(this.categories).forEach(category => {
scores[category] = 0;
let categoryWords = this.categories[category];
let total = Object.values(categoryWords).reduce((a, b) => a + b );
Object.keys(dataset).forEach(function (key) {
let value = dataset[key];
let s = categoryWords[key] || 0.1;
let i = 0;
while(i<value){
scores[category] += Math.log(s / parseFloat(total));
i++;
}
});
let s = this.categoryCounts[category] || 0.1;
scores[category] = (s / trainingCount);
});
return scores;
};
};
var b = new Bayes('good', 'bad');
b.train('good', { dry: 1, wet: 0 });
b.train('bad', { dry: 0, wet: 1 });
b.train('good', { dry: 0, wet: 1, green: 1});
b.train('good', { dry: 1, wet: 0, green: 1});
console.log(b.classify({ dry: 0, wet: 1, green: 2}));
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/64774083
复制相关文章
相似问题