{"id":478078,"date":"2023-08-09T09:27:06","date_gmt":"2023-08-09T09:27:06","guid":{"rendered":""},"modified":"2023-09-05T11:16:01","modified_gmt":"2023-09-05T11:16:01","slug":"multilabel-classification","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/ar\/wiki\/multilabel-classification\/","title":{"rendered":"\u062a\u0635\u0646\u064a\u0641 \u0645\u062a\u0639\u062f\u062f \u0627\u0644\u0639\u0644\u0627\u0645\u0627\u062a"},"content":{"rendered":"<p>\u064a\u0634\u064a\u0631 \u0627\u0644\u062a\u0635\u0646\u064a\u0641 \u0645\u062a\u0639\u062f\u062f \u0627\u0644\u062a\u0635\u0646\u064a\u0641\u0627\u062a \u0625\u0644\u0649 \u0645\u0647\u0645\u0629 \u062a\u0639\u064a\u064a\u0646 \u0645\u062c\u0645\u0648\u0639\u0629 \u0645\u0646 \u0627\u0644\u062a\u0635\u0646\u064a\u0641\u0627\u062a \u0627\u0644\u0645\u0633\u062a\u0647\u062f\u0641\u0629 \u0644\u0645\u062b\u064a\u0644 \u0648\u0627\u062d\u062f. \u0639\u0644\u0649 \u0639\u0643\u0633 \u0627\u0644\u062a\u0635\u0646\u064a\u0641 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\u0627\u0644\u062a\u0633\u0645\u064a\u0629<\/th>\n<th>\u062a\u0635\u0646\u064a\u0641 \u0645\u062a\u0639\u062f\u062f \u0627\u0644\u0637\u0628\u0642\u0627\u062a<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u062a\u0639\u064a\u064a\u0646 \u0627\u0644\u062a\u0633\u0645\u064a\u0629<\/td>\n<td>\u062a\u0633\u0645\u064a\u0627\u062a \u0645\u062a\u0639\u062f\u062f\u0629<\/td>\n<td>\u062a\u0633\u0645\u064a\u0629 \u0648\u0627\u062d\u062f\u0629<\/td>\n<\/tr>\n<tr>\n<td>\u062a\u0628\u0639\u064a\u0629 \u0627\u0644\u062a\u0633\u0645\u064a\u0629<\/td>\n<td>\u063a\u0627\u0644\u0628\u0627 \u0645\u0627 \u062a\u0643\u0648\u0646 \u0645\u0648\u062c\u0648\u062f\u0629<\/td>\n<td>\u063a\u064a\u0631 \u0645\u0648\u062c\u0648\u062f<\/td>\n<\/tr>\n<tr>\n<td>\u062a\u0639\u0642\u064a\u062f<\/td>\n<td>\u0623\u0639\u0644\u0649<\/td>\n<td>\u0623\u062f\u0646\u0649<\/td>\n<\/tr>\n<tr>\n<td>\u0627\u0644\u062e\u0648\u0627\u0631\u0632\u0645\u064a\u0627\u062a \u0627\u0644\u0645\u0634\u062a\u0631\u0643\u0629<\/td>\n<td>MLkNN\u060c \u0627\u0644\u0635\u0644\u0629 \u0627\u0644\u062b\u0646\u0627\u0626\u064a\u0629<\/td>\n<td>SVM\u060c \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0627\u0644\u0644\u0648\u062c\u0633\u062a\u064a<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\u0648\u062c\u0647\u0627\u062a \u0646\u0638\u0631 \u0648\u062a\u0642\u0646\u064a\u0627\u062a \u0627\u0644\u0645\u0633\u062a\u0642\u0628\u0644 \u0627\u0644\u0645\u062a\u0639\u0644\u0642\u0629 \u0628\u0627\u0644\u062a\u0635\u0646\u064a\u0641 \u0645\u062a\u0639\u062f\u062f \u0627\u0644\u0639\u0644\u0627\u0645\u0627\u062a<\/h2>\n<p>\u0625\u0646 \u0645\u0633\u062a\u0642\u0628\u0644 \u0627\u0644\u062a\u0635\u0646\u064a\u0641 \u0645\u062a\u0639\u062f\u062f \u0627\u0644\u0639\u0644\u0627\u0645\u0627\u062a \u0648\u0627\u0639\u062f\u060c \u0645\u0639 \u0627\u0633\u062a\u0645\u0631\u0627\u0631 \u0627\u0644\u0628\u062d\u062b \u0641\u064a \u0627\u0644\u0645\u062c\u0627\u0644\u0627\u062a \u0627\u0644\u062a\u0627\u0644\u064a\u0629:<\/p>\n<ul>\n<li>\u062a\u0642\u0646\u064a\u0627\u062a \u0627\u0644\u062a\u0639\u0644\u0645 \u0627\u0644\u0639\u0645\u064a\u0642 \u0645\u0635\u0645\u0645\u0629 \u062e\u0635\u064a\u0635\u064b\u0627 \u0644\u0644\u0645\u0647\u0627\u0645 \u0645\u062a\u0639\u062f\u062f\u0629 \u0627\u0644\u062a\u0635\u0646\u064a\u0641\u0627\u062a.<\/li>\n<li>\u0627\u0644\u062a\u0639\u0627\u0645\u0644 \u0628\u0643\u0641\u0627\u0621\u0629 \u0645\u0639 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0648\u0627\u0633\u0639\u0629 \u0627\u0644\u0646\u0637\u0627\u0642 \u0648\u0639\u0627\u0644\u064a\u0629 \u0627\u0644\u0623\u0628\u0639\u0627\u062f.<\/li>\n<li>\u0623\u0633\u0627\u0644\u064a\u0628 \u0627\u0644\u062a\u0643\u064a\u0641 \u0644\u0644\u062a\u0639\u0627\u0645\u0644 \u0645\u0639 \u0645\u0633\u0627\u062d\u0627\u062a \u0627\u0644\u062a\u0633\u0645\u064a\u0629 \u0627\u0644\u0645\u062a\u0637\u0648\u0631\u0629.<\/li>\n<li>\u0627\u0644\u062a\u0643\u0627\u0645\u0644 \u0645\u0639 \u0627\u0644\u062a\u0639\u0644\u0645 \u063a\u064a\u0631 \u0627\u0644\u062e\u0627\u0636\u0639 \u0644\u0644\u0631\u0642\u0627\u0628\u0629 \u0644\u0646\u0645\u0627\u0630\u062c \u0623\u0643\u062b\u0631 \u0642\u0648\u0629.<\/li>\n<\/ul>\n<h2>\u0643\u064a\u0641 \u064a\u0645\u0643\u0646 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062e\u0648\u0627\u062f\u0645 \u0627\u0644\u0648\u0643\u064a\u0644\u0629 \u0623\u0648 \u0631\u0628\u0637\u0647\u0627 \u0628\u0627\u0644\u062a\u0635\u0646\u064a\u0641 \u0627\u0644\u0645\u062a\u0639\u062f\u062f \u0627\u0644\u062a\u0635\u0646\u064a\u0641\u0627\u062a<\/h2>\n<p>\u064a\u0645\u0643\u0646 \u0644\u0644\u062e\u0648\u0627\u062f\u0645 \u0627\u0644\u0648\u0643\u064a\u0644\u0629 \u0645\u062b\u0644 OneProxy \u0623\u0646 \u062a\u0644\u0639\u0628 \u062f\u0648\u0631\u064b\u0627 \u0641\u064a \u0645\u0647\u0627\u0645 \u0627\u0644\u062a\u0635\u0646\u064a\u0641 \u0645\u062a\u0639\u062f\u062f \u0627\u0644\u062a\u0635\u0646\u064a\u0641\u0627\u062a\u060c \u062e\u0627\u0635\u0629 \u0641\u064a \u0639\u0645\u0644\u064a\u0627\u062a \u062a\u062c\u0631\u064a\u0641 \u0627\u0644\u0648\u064a\u0628 \u0623\u0648 \u0639\u0645\u0644\u064a\u0627\u062a \u062c\u0645\u0639 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a.<\/p>\n<ul>\n<li><strong>\u0625\u062e\u0641\u0627\u0621 \u0647\u0648\u064a\u0629 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a:<\/strong> \u064a\u0645\u0643\u0646 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062e\u0648\u0627\u062f\u0645 \u0627\u0644\u0648\u0643\u064a\u0644\u0629 \u0644\u062c\u0645\u0639 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0628\u0634\u0643\u0644 \u0645\u062c\u0647\u0648\u0644\u060c \u0648\u0627\u0644\u062d\u0641\u0627\u0638 \u0639\u0644\u0649 \u0627\u0644\u062e\u0635\u0648\u0635\u064a\u0629.<\/li>\n<li><strong>\u0627\u0644\u0645\u0639\u0627\u0644\u062c\u0629 \u0627\u0644\u0645\u062a\u0648\u0627\u0632\u064a\u0629:<\/strong> \u064a\u0645\u0643\u0646 \u0623\u0646 \u064a\u0624\u062f\u064a \u062a\u0648\u0632\u064a\u0639 \u0627\u0644\u0637\u0644\u0628\u0627\u062a \u0639\u0628\u0631 \u0648\u0643\u0644\u0627\u0621 \u0645\u062e\u062a\u0644\u0641\u064a\u0646 \u0625\u0644\u0649 \u062a\u0633\u0631\u064a\u0639 \u0639\u0645\u0644\u064a\u0629 \u062c\u0645\u0639 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0644\u0646\u0645\u0627\u0630\u062c \u0627\u0644\u062a\u062f\u0631\u064a\u0628.<\/li>\n<li><strong>\u0627\u0644\u0648\u0635\u0648\u0644 \u0627\u0644\u0639\u0627\u0644\u0645\u064a:<\/strong> \u062a\u0639\u0645\u0644 \u0627\u0644\u0648\u0643\u0644\u0627\u0621 \u0639\u0644\u0649 \u062a\u0645\u0643\u064a\u0646 \u062c\u0645\u0639 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u062e\u0627\u0635\u0629 \u0628\u0627\u0644\u0645\u0646\u0637\u0642\u0629\u060c \u0645\u0645\u0627 \u064a\u0633\u0645\u062d \u0628\u0645\u062c\u0645\u0648\u0639\u0627\u062a \u062a\u062f\u0631\u064a\u0628 \u0623\u0643\u062b\u0631 \u062f\u0642\u0629 \u0648\u062a\u0646\u0648\u0639\u064b\u0627.<\/li>\n<\/ul>\n<h2>\u0631\u0648\u0627\u0628\u0637 \u0630\u0627\u062a \u0639\u0644\u0627\u0642\u0629<\/h2>\n<ol>\n<li><a href=\"http:\/\/link-to-paper.com\" target=\"_new\" rel=\"noopener nofollow\">\u0648\u0631\u0642\u0629 \u0634\u0627\u0628\u064a\u0631 \u0648\u0633\u0646\u062c\u0631 \u062d\u0648\u0644 \u0627\u0644\u062a\u0635\u0646\u064a\u0641 \u0645\u062a\u0639\u062f\u062f \u0627\u0644\u0639\u0644\u0627\u0645\u0627\u062a<\/a><\/li>\n<li><a href=\"https:\/\/scikit-learn.org\/stable\/modules\/multiclass.html\" target=\"_new\" rel=\"noopener nofollow\">\u062f\u0644\u064a\u0644 Scikit-Learn \u0644\u0644\u062a\u0635\u0646\u064a\u0641 \u0645\u062a\u0639\u062f\u062f \u0627\u0644\u062a\u0635\u0646\u064a\u0641\u0627\u062a<\/a><\/li>\n<li><a href=\"https:\/\/oneproxy.pro\/ar\/guide-to-proxy-use-in-ml\/\" target=\"_new\" rel=\"noopener\">\u062f\u0644\u064a\u0644 OneProxy \u062d\u0648\u0644 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0648\u0643\u064a\u0644 \u0641\u064a \u0627\u0644\u062a\u0639\u0644\u0645 \u0627\u0644\u0622\u0644\u064a<\/a><\/li>\n<\/ol>\n<p>\u0645\u0646 \u062e\u0644\u0627\u0644 \u0627\u0644\u062e\u0648\u0636 \u0641\u064a \u0627\u0644\u062a\u0639\u0642\u064a\u062f \u0648\u0627\u0644\u0623\u0633\u0627\u0644\u064a\u0628 \u0648\u0627\u0644\u062a\u0637\u0628\u064a\u0642\u0627\u062a \u0648\u0627\u0644\u0627\u062a\u062c\u0627\u0647\u0627\u062a \u0627\u0644\u0645\u0633\u062a\u0642\u0628\u0644\u064a\u0629 \u0644\u0644\u062a\u0635\u0646\u064a\u0641 \u0645\u062a\u0639\u062f\u062f \u0627\u0644\u0639\u0644\u0627\u0645\u0627\u062a\u060c \u064a\u0635\u0628\u062d \u0645\u0646 \u0627\u0644\u0648\u0627\u0636\u062d \u0645\u062f\u0649 \u0623\u0647\u0645\u064a\u0629 \u0647\u0630\u0627 \u0627\u0644\u0645\u062c\u0627\u0644 \u0648\u062a\u0637\u0648\u0631\u0647. \u0625\u0646 \u062f\u0648\u0631 \u0627\u0644\u062e\u0648\u0627\u062f\u0645 \u0627\u0644\u0648\u0643\u064a\u0644\u0629 \u0645\u062b\u0644 OneProxy \u0641\u064a \u062a\u0639\u0632\u064a\u0632 \u062c\u0645\u0639 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0648\u062a\u062d\u0644\u064a\u0644\u0647\u0627 \u064a\u0632\u064a\u062f \u0645\u0646 \u0625\u062b\u0631\u0627\u0621 \u0627\u0644\u0645\u0634\u0647\u062f \u0645\u062a\u0639\u062f\u062f \u0627\u0644\u0623\u0648\u062c\u0647 \u0644\u0644\u062a\u0635\u0646\u064a\u0641 \u0645\u062a\u0639\u062f\u062f \u0627\u0644\u062a\u0635\u0646\u064a\u0641\u0627\u062a.<\/p>","protected":false},"featured_media":468953,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-478078","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Multilabel Classification<\/mark>","faq_items":[{"question":"What is Multilabel Classification?","answer":"<p>Multilabel classification refers to the task of categorizing instances into multiple labels simultaneously. It differs from multiclass classification, where an instance is assigned to only one category.<\/p>"},{"question":"What is the History of Multilabel Classification?","answer":"<p>Multilabel classification originated in the early 2000s, with the first known paper on the subject published by Schapire and Singer in 1999. This paper laid the groundwork for future research in the area.<\/p>"},{"question":"How Does Multilabel Classification Work?","answer":"<p>Multilabel classification works by assigning multiple target labels to a single instance. Different algorithms like Binary Relevance, Classifier Chains, Label Powerset, and customized Neural Networks are used to accomplish this task.<\/p>"},{"question":"What Are the Key Features of Multilabel Classification?","answer":"<p>The key features of multilabel classification include its complexity due to multiple labels, potential interdependencies between labels, specific evaluation metrics such as precision and recall, and the challenge of label imbalance.<\/p>"},{"question":"What Types of Multilabel Classification Exist?","answer":"<p>Several strategies handle the multilabel classification task, including Binary Relevance, Classifier Chains, Label Powerset, and Neural Networks designed specifically for multilabel problems.<\/p>"},{"question":"How Is Multilabel Classification Used and What Are the Associated Problems and Solutions?","answer":"<p>Multilabel classification is used in content tagging, healthcare, e-commerce, and other areas. Problems can include label imbalance, computational complexity, and label correlations. These can be addressed through resampling, dimensionality reduction, and utilizing models that capture label dependencies.<\/p>"},{"question":"How Does Multilabel Classification Compare to Multiclass Classification?","answer":"<p>While multilabel classification allows for multiple labels for a single instance and often has label dependencies, multiclass classification assigns only a single label to each instance and does not consider label dependencies.<\/p>"},{"question":"What Are the Future Perspectives and Technologies Related to Multilabel Classification?","answer":"<p>The future of multilabel classification is bright, with ongoing research in deep learning techniques, efficient handling of large-scale data, adaptive methods for evolving label spaces, and integration with unsupervised learning.<\/p>"},{"question":"How Can Proxy Servers Like OneProxy Be Associated with Multilabel Classification?","answer":"<p>Proxy servers like OneProxy can be used in multilabel classification tasks for data anonymization, parallel processing, and global reach in data collection. They facilitate web scraping or data collection processes, contributing to more effective model training.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/ar\/wp-json\/wp\/v2\/wiki\/478078","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/ar\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/ar\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/ar\/wp-json\/wp\/v2\/wiki\/478078\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/ar\/wp-json\/wp\/v2\/media\/468953"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/ar\/wp-json\/wp\/v2\/media?parent=478078"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}