{"id":12071,"date":"2022-09-29T12:51:56","date_gmt":"2022-09-29T07:21:56","guid":{"rendered":"https:\/\/jassweb.com\/solved\/solved-valueerror-shapes-41551445-and-45877-not-aligned-1445-dim-1-4587-dim-0\/"},"modified":"2022-09-29T12:51:56","modified_gmt":"2022-09-29T07:21:56","slug":"solved-valueerror-shapes-41551445-and-45877-not-aligned-1445-dim-1-4587-dim-0","status":"publish","type":"post","link":"https:\/\/jassweb.com\/solved\/solved-valueerror-shapes-41551445-and-45877-not-aligned-1445-dim-1-4587-dim-0\/","title":{"rendered":"[Solved] ValueError: shapes (4155,1445) and (4587,7) not aligned: 1445 (dim 1) != 4587 (dim 0)"},"content":{"rendered":"<p> [ad_1]<br \/>\n<\/p>\n<div id=\"answer-56618044\" class=\"answer js-answer accepted-answer js-accepted-answer\" data-answerid=\"56618044\" data-parentid=\"56617715\" data-score=\"1\" data-position-on-page=\"1\" data-highest-scored=\"1\" data-question-has-accepted-highest-score=\"1\" itemprop=\"acceptedAnswer\" itemscope itemtype=\"https:\/\/schema.org\/Answer\">\n<div class=\"post-layout\">\n<div class=\"votecell post-layout--left\"><\/div>\n<div class=\"answercell post-layout--right\">\n<div class=\"s-prose js-post-body\" itemprop=\"text\">\n<p>Have a look at the sci-kit learn documentation for <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/scikit-learn.org\/stable\/modules\/generated\/sklearn.naive_bayes.MultinomialNB.html\">Multinomial NB<\/a>.<\/p>\n<p>It clearly specifies the structure of the input data while trainig <code>model.fit()<\/code> must match the structure of the input data while testing or scoring <code>model.predict()<\/code>.<\/p>\n<p>This means that you cannot use the same model for different dataset. The only way this is possible is that both the dataset have the same features (same number of features and in the same order as the training dataset).<\/p>\n<p>In your case this is not going to work as the datasets are different which is visible from the shape of the two datasets.<\/p>\n<pre><code>Set 1 has 4587 features\nSet 2 has 1445 features\n<\/code><\/pre>\n<p>Make sure the both the dataset have the same number of features and in the same order as the training set.<\/p>\n<\/p><\/div>\n<div class=\"mt24\"><\/div>\n<\/div>\n<p>            <span class=\"d-none\" itemprop=\"commentCount\"><\/span> <\/p><\/div>\n<\/div>\n<p>[ad_2]<\/p>\n<p>solved ValueError: shapes (4155,1445) and (4587,7) not aligned: 1445 (dim 1) != 4587 (dim 0) <\/p>\n","protected":false},"excerpt":{"rendered":"<p>[ad_1] Have a look at the sci-kit learn documentation for Multinomial NB. It clearly specifies the structure of the input data while trainig model.fit() must match the structure of the input data while testing or scoring model.predict(). This means that you cannot use the same model for different dataset. The only way this is possible &#8230; <a title=\"[Solved] ValueError: shapes (4155,1445) and (4587,7) not aligned: 1445 (dim 1) != 4587 (dim 0)\" class=\"read-more\" href=\"https:\/\/jassweb.com\/solved\/solved-valueerror-shapes-41551445-and-45877-not-aligned-1445-dim-1-4587-dim-0\/\" aria-label=\"More on [Solved] ValueError: shapes (4155,1445) and (4587,7) not aligned: 1445 (dim 1) != 4587 (dim 0)\">Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[320],"tags":[1173,3292,482,792],"class_list":["post-12071","post","type-post","status-publish","format-standard","hentry","category-solved","tag-machine-learning","tag-naivebayes","tag-python-3-x","tag-scikit-learn"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>[Solved] ValueError: shapes (4155,1445) and (4587,7) not aligned: 1445 (dim 1) != 4587 (dim 0) - JassWeb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/jassweb.com\/solved\/solved-valueerror-shapes-41551445-and-45877-not-aligned-1445-dim-1-4587-dim-0\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"[Solved] ValueError: shapes (4155,1445) and (4587,7) not aligned: 1445 (dim 1) != 4587 (dim 0) - JassWeb\" \/>\n<meta property=\"og:description\" content=\"[ad_1] Have a look at the sci-kit learn documentation for Multinomial NB. It clearly specifies the structure of the input data while trainig model.fit() must match the structure of the input data while testing or scoring model.predict(). This means that you cannot use the same model for different dataset. The only way this is possible ... 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