🔥 预测任务索引帖
待完善 #refplus, #refplus li{ padding:0; margin:0; list-style:none; }； document.querySelectorAll(".refplus-num").forEach((ref) => { let refid = ref.firstChild.href.replace(location.origin+location.pathname,''); let refel = document.querySelector(refid); let refnum = refel.dataset.num; let ref_content = refel.innerText.replace(`[${refnum}]`,''); tippy(ref, { content:...
生成任务索引帖
待完善 #refplus, #refplus li{ padding:0; margin:0; list-style:none; }； document.querySelectorAll(".refplus-num").forEach((ref) => { let refid = ref.firstChild.href.replace(location.origin+location.pathname,''); let refel = document.querySelector(refid); let refnum = refel.dataset.num; let ref_content = refel.innerText.replace(`[${refnum}]`,''); tippy(ref, { content:...
发现任务索引帖
待完善 #refplus, #refplus li{ padding:0; margin:0; list-style:none; }； document.querySelectorAll(".refplus-num").forEach((ref) => { let refid = ref.firstChild.href.replace(location.origin+location.pathname,''); let refel = document.querySelector(refid); let refnum = refel.dataset.num; let ref_content = refel.innerText.replace(`[${refnum}]`,''); tippy(ref, { content:...
非参数贝叶斯模型索引帖
#refplus, #refplus li{ padding:0; margin:0; list-style:none; }； document.querySelectorAll(".refplus-num").forEach((ref) => { let refid = ref.firstChild.href.replace(location.origin+location.pathname,''); let refel = document.querySelector(refid); let refnum = refel.dataset.num; let ref_content = refel.innerText.replace(`[${refnum}]`,''); tippy(ref, { content: ref_content, ...
神经网络索引帖
#refplus, #refplus li{ padding:0; margin:0; list-style:none; }； document.querySelectorAll(".refplus-num").forEach((ref) => { let refid = ref.firstChild.href.replace(location.origin+location.pathname,''); let refel = document.querySelector(refid); let refnum = refel.dataset.num; let ref_content = refel.innerText.replace(`[${refnum}]`,''); tippy(ref, { content: ref_content, ...
非独立同分布索引帖
#refplus, #refplus li{ padding:0; margin:0; list-style:none; }； document.querySelectorAll(".refplus-num").forEach((ref) => { let refid = ref.firstChild.href.replace(location.origin+location.pathname,''); let refel = document.querySelector(refid); let refnum = refel.dataset.num; let ref_content = refel.innerText.replace(`[${refnum}]`,''); tippy(ref, { content: ref_content, ...
非独立同分布索引帖
#refplus, #refplus li{ padding:0; margin:0; list-style:none; }； document.querySelectorAll(".refplus-num").forEach((ref) => { let refid = ref.firstChild.href.replace(location.origin+location.pathname,''); let refel = document.querySelector(refid); let refnum = refel.dataset.num; let ref_content = refel.innerText.replace(`[${refnum}]`,''); tippy(ref, { content: ref_content, ...
模型选择与平均索引帖
#refplus, #refplus li{ padding:0; margin:0; list-style:none; }； document.querySelectorAll(".refplus-num").forEach((ref) => { let refid = ref.firstChild.href.replace(location.origin+location.pathname,''); let refel = document.querySelector(refid); let refnum = refel.dataset.num; let ref_content = refel.innerText.replace(`[${refnum}]`,''); tippy(ref, { content: ref_content, ...
🔥 广义线性模型索引帖
待补充 #refplus, #refplus li{ padding:0; margin:0; list-style:none; }； document.querySelectorAll(".refplus-num").forEach((ref) => { let refid = ref.firstChild.href.replace(location.origin+location.pathname,''); let refel = document.querySelector(refid); let refnum = refel.dataset.num; let ref_content = refel.innerText.replace(`[${refnum}]`,''); tippy(ref, { content:...
非参数模型索引帖
【摘要】非参数模型并不是指模型没有参数，而是指模型中没有固定数量的参数，所以称之为无固定数量参数模型更为准确一些。传统的非参数模型主要包括以下三种类型：基于样本实例的模型（如 KNN 等）、基于核函数的模型（如：高斯过程、支持向量机）、基于决策树的模型（如：分类树、回归树、随机森林等），本文讲对它们进行概览。关于各种模型的细节，参加下面的相关链接。 【相关链接】 基于实例的方法： KNN 算法 距离度量方法 KDE 算法 基于核函数的方法： 高斯过程 支持向量机 基于决策树的方法： 分类树 回归树 随机森林 p{text-indent:2em;2} 1 非参数模型概述 #refplus, #refplus li{ padding:0; margin:0; list-style:none; }； document.querySelectorAll(".refplus-num").forEach((ref) => { ...