[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121418-en":3,"doc-seo-121418-105":30,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121418,962075114765,"Quinn","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",6,"Technology","A machine learning software tool for multiclass classification - code and workflow","This paper provides code for a published multiclass classification study and explains the accompanying workflow for researchers. Implementations cover five traditional machine learning models (LR, KNN, NB, RF, XGBoost) and two deep learning models (MLP, CNN). The example uses administrative healthcare data and evaluates performance with accuracy, precision, recall, and F1-score. Feature importance, feature correlation, variable clustering, confusion matrix analysis, and kernel density estimation support interpretation, helping stakeholders mitigate harm from disease comorbidity and multimorbidity.","Original software publication  \nA machine learning software tool for multiclass classification  Shangzhou Wang a, Haohui Lua, Arif Khana, Farshid Hajatib, Matloob Khushic,d, Shahadat Uddina,∗  \na School of Project Management, Faculty of Engineering, The University of Sydney, Level 2, 21 Ross Street, Forest Lodge, NSW 2037, Australia b College of Engineering and Science, Victoria University Sydney, 160 Sussex Street, Sydney, NSW 2000, Australia  \nc University of Suffolk, Ipswich, UK  \nd School of Computer Science, The University of Sydney, Australia  \n| A R T I C L E I N F O\u003Cbr>Keywords:\u003Cbr>Disease comorbidity\u003Cbr>Disease multimorbidity Machine learning Multiclass classification | A B S T R A C T |\n| --- | --- |\n|  | This paper describes code for a published article that can assist researchers with multiclass classification problems and analyse the performances of various machine learning models. Further, feature importance, feature correlation, variable clustering, confusion matrix and kernel density estimation were also implemented. The original study was published in Expert Systems with Applications, and this paper explains the code and workflow. Administrative healthcare data has been used as an example to run the code. The results and insights can assist healthcare stakeholders and policymakers reduce the negative impact of illness comorbidity and multimorbidity. |\n\nCode metadata  \n\n| Current code version | V1.0 |\n| --- | --- |\n| Permanent link to code/repository used for this code version | [https://github.com/SoftwareImpacts/SIMPAC-2022-108](https://github.com/SoftwareImpacts/SIMPAC-2022-108) |\n| Permanent link to reproducible capsule | [https://codeocean.com/capsule/3697326/tree/v1](https://codeocean.com/capsule/3697326/tree/v1) |\n| Legal code license | MIT License |\n| Code versioning system used |  |\n| Software code languages, tools and services used | Python |\n| Compilation requirements, operating environments and dependencies If available, link to developer documentation/manual | Pandas, Keras, scikit-learn, TensorFlow, NumPy, matplotlib, seaborn, XGboost |\n| Support email for questions | [shahadat.uddin@sydney.edu.au](shahadat.uddin@sydney.edu.au) |\n\n1. Introduction  \nData has fundamentally altered how people live and conduct business in the 21st century. Data have been used in many sectors to address practical problems, including predicting disease in healthcare [1–3], assisting policymakers in making decisions [4], and predicting corporate bankruptcy [5]. Chronic diseases are becoming more prevalent throughout the world, various disease burdens are rising, and the social and economic consequences will have an impact on people’s quality of life. In many circumstances, the existence of one chronic disease  \nleads to the development of one or more other chronic disorders, which significantly strains global healthcare systems.  \nThis paper describes the models developed by Uddin et al. [6] and how these models can be applied to new datasets related to disease comorbidity or multimorbidity. Disease comorbidity is described asthe presence of many diseases simultaneously. An individual who has more than two comorbidities is referred to as multimorbid. Obtaining good quality prediction performance is a key and critical factor when determining whether a patient will be diagnosed with comorbidity or multimorbidity. However, we intend to delve into deeper detail in our  \nThe code (and data) in this article has been certified as Reproducible by Code Ocean: ([https://codeocean.com/](https://codeocean.com/)). More information on the Reproducibility Badge Initiative is available at [https://www.elsevier.com/physical-sciences-and-engineering/computer-science/journals](https://www.elsevier.com/physical-sciences-and-engineering/computer-science/journals).  \n∗ Corresponding author.  \nE-mail addresses: [steven.wang1@iqvia.com](steven.wang1@iqvia.com) (S. Wang), [haohui.lu@sydney.edu.au](haohui.lu@sydney.edu.au) (H. Lu), [arif.khan@syd","cbCaijCvgMjjLmnJ","https://ap.wps.com/l/cbCaijCvgMjjLmnJ","pdf",537255,1,4,"English","en",105,"# Introduction\n## Disease comorbidity and multimorbidity\n## Software overview and implemented models\n# Functionalities\n## Data loading and library setup\n## Model execution and performance evaluation\n# Interpretability analyses\n## Feature importance and correlation\n## Variable clustering and confusion matrix\n## Kernel density estimation","[{\"question\":\"What models does the software tool implement for multiclass classification?\",\"answer\":\"It implements five classic models (Logistic regression, KNN, Naïve Bayes, Random forest, XGBoost) and two deep learning models (MLP and CNN).\"},{\"question\":\"How is model performance evaluated in this workflow?\",\"answer\":\"Performance is compared using accuracy, precision, recall, and F1-score across the implemented models.\"},{\"question\":\"Which interpretability techniques are included for the best-performing model?\",\"answer\":\"The workflow includes feature importance, feature correlation, variable clustering, confusion matrix analysis, and kernel density estimation.\"}]","A machine learning software tool for multiclass classification - code and workflow | PDF",1785735578,10,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":28},"a-machine-learning-software-tool-for-multiclass-classification-code-and-workflow","",{"@graph":36,"@context":84},[37,53,67],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/technology/",3,{"item":52,"name":13,"@type":43,"position":21},"https://docshare.wps.com/document/a-machine-learning-software-tool-for-multiclass-classification-code-and-workflow/121418/",{"url":52,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"What models does the software tool implement for multiclass classification?","Question",{"text":74,"@type":75},"It implements five classic models (Logistic regression, KNN, Naïve Bayes, Random forest, XGBoost) and two deep learning models (MLP and CNN).","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"How is model performance evaluated in this workflow?",{"text":79,"@type":75},"Performance is compared using accuracy, precision, recall, and F1-score across the implemented models.",{"name":81,"@type":72,"acceptedAnswer":82},"Which interpretability techniques are included for the best-performing model?",{"text":83,"@type":75},"The workflow includes feature importance, feature correlation, variable clustering, confusion matrix analysis, and kernel density estimation.","https://schema.org",{"og:url":52,"og:type":86,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":88,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":91},[92,96,100,104,109,112,117,122,127,130,133],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":110,"slug":111},50,"technology",{"id":113,"doc_module":4,"doc_module_name":46,"category_name":114,"show_sort_weight":115,"slug":116},7,"Healthcare",40,"healthcare",{"id":118,"doc_module":4,"doc_module_name":46,"category_name":119,"show_sort_weight":120,"slug":121},8,"Research & Report",30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":29,"doc_module":4,"doc_module_name":46,"category_name":131,"show_sort_weight":29,"slug":132},"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":46,"category_name":135,"show_sort_weight":105,"slug":136},19,"General","general"]