{"version":"1.0","provider_name":"JassWeb","provider_url":"https:\/\/jassweb.com\/solved","author_name":"Kirat","author_url":"https:\/\/jassweb.com\/solved\/author\/jaspritsinghghumangmail-com\/","title":"[Solved] Neural network output is always 1 - JassWeb","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"CsatRvuSMn\"><a href=\"https:\/\/jassweb.com\/solved\/solved-neural-network-output-is-always-1\/\">[Solved] Neural network output is always 1<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/jassweb.com\/solved\/solved-neural-network-output-is-always-1\/embed\/#?secret=CsatRvuSMn\" width=\"600\" height=\"338\" title=\"&#8220;[Solved] Neural network output is always 1&#8221; &#8212; JassWeb\" data-secret=\"CsatRvuSMn\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/jassweb.com\/solved\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","description":"[ad_1] I didn&#8217;t check your code but&#8230; No, you can&#8217;t use fixed weight like that. Each node in your hidden layer will get larger and larger values as you increase the amount of inputs. Sigmoid will scale the large values to 1. Think about it: Let&#8217;s say that you have 100 inputs each having &#8220;random&#8221; ... Read more"}