R Code Review for Random Forest Model

@ShaikhAneesa

Hi there, I’ve carefully reviewed your requirements and understand that you already have the research methodology defined, so the real need is an experienced R reviewer who can verify that the implementation correctly reflects the intended predictive methodology and is not introducing avoidable bias or performance issues. I’m confident I can audit the code at both the programming and statistical-modeling level. My approach will be to first review the complete R workflow, data preparation, feature handling, model training, and validation logic. Then, I’ll audit the implementation of Firth’s CoxPH, Elastic Net, SVM, AFT, RSF, and boosting models, including preprocessing, tuning, censoring, assumptions, and leakage risks. Next, I’ll evaluate prediction and validation metrics and identify opportunities to improve efficiency, reproducibility, and predictive reliability. Finally, I’ll provide clear code-level corrections and detailed recommendations with the reasoning behind each change. You’ll receive a thoroughly reviewed R workflow, prioritized corrections, model-validation feedback, and practical recommendations you can apply to the research project. Could you share the current R code and project methodology so I can assess how closely the implementation matches your intended analysis? Send the code over, and let’s validate the modelling pipeline properly before you invest further in the analysis. Warm Regards, Aneesa.

@WycOj

As a seasoned Biostatistician, Data Analyst and Researcher with a solid background in data science, I believe I would be an excellent fit for your code review project. My specialization in R programming language, statistical analysis, and predictive modeling aligns perfectly with your needs. With over 7 years of experience, including working on sophisticated experiments like those involving Firth's coxph, Enet, svm, aft, rsf and boosting models, I guarantee both efficiency and clarity in reviewing your code. Beyond reviewing code for accuracy, I also emphasize the optimization of predictive models. My approach involves meticulous data cleaning and coding to ensure the best results. Additionally, my proficiency extends to deep learning and NLP modeling – crucial in classification and regression tasks. While your budget is limited as a self-funded research project, I assure you top-notch quality within tight timelines. Over my career I have built up exceptional skills working on complex healthcare datasets. Aside from that, my versatility enables me to provide services in numerous software packages such as R studio and Tableau among others as stated above making me your one stop shop solution for this work as I am available 24/7 delivering quality work within time limits. With my expertise, a thorough resolution of your concerns is guaranteed while keeping your research project moving forward efficiently. Let's get started!

@belarjsoufiane20

I can review your R code thoroughly to ensure the predictive modeling workflow is statistically sound, accurate, and aligned with your research objectives. I hold a Master’s degree in Statistics and have over 7 years of experience with R, predictive modeling, and statistical analysis. I can review the implementation of Firth’s Cox models, Elastic Net, SVM, AFT, Random Survival Forests, and boosting, including preprocessing, model fitting, validation, performance metrics, and potential sources of bias or overfitting. I’ll provide clear recommendations and corrected/optimized code where necessary. I also understand this is self-funded research and can work within a reasonable budget.

@glanegonsalves

Hi, Glane here. I can review your existing R predictive modeling code with a focus on correctness, prediction performance, efficiency, and reproducibility. I’m familiar with workflows involving Firth’s Cox regression, Elastic Net, SVM, AFT, Random Survival Forests, and boosting, and can check the implementation against your stated methodology rather than changing the research approach unnecessarily. I’ll identify coding or modelling issues, data leakage risks, validation problems, and opportunities to improve predictive accuracy, then provide clear recommendations and corrected code where needed. I understand this is a self-funded research project, so I’m happy to work within a limited budget.

@eldadshericks

Dear client, I am a Data Analyst by profession, and by using R, I can help you uncover insights from your data. I run both quantitative and qualitative analyses professionally. I am proficient in R's robust statistical modeling packages, such as lm and glm, to implement the necessary models and algorithms. This enables me to provide you with a comprehensive analysis report that includes the results of the statistical modeling performed on your dataset. My reports present key findings, insights, and relevant visualizations to aid in your decision-making process, using clear explanations and comments within the code to enhance comprehension. Please get in touch so we can proceed with the project.

@Fazeennazar

Hello I checked your project and the main requirement is to review your existing R predictive-modeling code for correctness, efficiency, clarity, and whether the implementation properly matches your research methodology. I have experience with Python-based data analysis and predictive workflows, and I can apply a structured code-review approach to check data preparation, feature handling, model configuration, validation, and prediction logic. I would carefully review the Random Forest/RSF implementation along with the Firth CoxPH, Elastic Net, SVM, AFT, and boosting components where applicable, looking for methodological or coding issues that could affect prediction performance. I would provide specific feedback on potential accuracy problems, inefficient sections, validation strategy, and practical improvements rather than simply rewriting the code. If you share the current R scripts and methodology, I can review them together so the recommendations remain aligned with the purpose of your research. Best regards.

@DevDataAnalyst

Hi, I have 12 years of working experience in R, KNIME Analytics, Tableau Desktop/Server, SQL Server, Tableau Prep. I have developed Analytics Solutions and designed professional quality ETL workflows for different clients. Looking forward to discussing the requirements in detail Thanks, Drik

@adeelpirzada

Hi, I am Adeel. My background is applied predictive analytics, including model evaluation and diagnostics work in Python and R style pipelines, so reading someone else's modeling code for correctness rather than just style is familiar ground. I would start by checking the modeling assumptions for each method, especially the Cox and survival models, then verify the validation and metric code before touching efficiency or style. Given the budget I would scope this to a focused review of the core model fitting and evaluation sections rather than the entire codebase end to end. How many separate model scripts are you looking to have reviewed, one or several?

@ImranAli01

Hello, I got that you need an R expert to audit predictive-model code across Firth’s CoxPH, Elastic Net, SVM, AFT, RSF, and boosting, with the main goal of validating correctness and improving prediction accuracy. This is what I can help you with, let's chat. My approach is to review the R pipeline from data preparation through model fitting, validation, tuning, and prediction, checking for implementation errors, leakage, incorrect assumptions, and inefficient code. I will specifically examine model-specific settings, preprocessing, feature handling, resampling, hyperparameter tuning, and performance metrics, then test the corrected workflow against the intended methodology. The review will produce concrete code-level changes and explain how each recommendation affects predictive reliability rather than simply improving code style. As final deliverables you will receive a thoroughly reviewed R codebase, identified issues, corrected implementations where required, model-validation findings, and detailed recommendations for improving prediction performance. One thing I'd like to confirm before we start: Will you provide the project methodology and dataset alongside the existing R code? Let's have a quick chat to review the current implementation. Best Regards, Imran

@khaliduom103

‎Hi i am an experienced R and Rstudio analyst for regression analyst  with PhD in applied mathematics and data analyst.I can help your data in R coding, optimization, numerical analysis،simulation of the CSV files. ‎

@devendrathakur12

Hi, I’m Dev Singh, a Principal Software Engineer with 20+ years in AI, ML and predictive modeling. I have gone through your specific requirement for R predictive model code review. I would review the existing R code before changing methods, since a model can look accurate while data leakage makes its results misleading. I will check your Firth’s coxph and Enet code first, then review the other drafted methods against your stated research goals. And I will focus on prediction validity as well as code clarity, at least that is where I would start. I can send project details privately. Which R packages and versions are you using for the listed models? Do you have a held-out test set, or are you currently assessing performance through cross-validation? What outcome and prediction metric does your research outline define as the main target? Free for a quick call? Or answer here and I will suggest the first review steps. Dev Singh

@pebambang5

Hello, I have read the detail of your project, and I’m sure can solve the task, provide correct result, free revision guarantee. My background is in statistics and applied mathematics using R programming for model statistics, predictive analytics, machine learning and artificial intelligence. I’m an expert in various model regression, will work based on your "Key Requirements", and fulfill "Ideal Skills and Experience:". Please share your data, I'm available, budget/time negotiable. Thank you. Best rgds, Bambangpe

@goprosol

I understand that you are looking for an R expert to review your code for predictive models, focusing on accuracy. With a detailed project outline and methods drafted, my expertise in R and predictive models, including Firth's coxph, Enet, svm, aft, rsf, and boosting, aligns well with your requirements. As a PhD Scholar and Lecturer with a strong background in predictive modeling and data analysis, I am well-equipped to review your code for efficiency and clarity, providing detailed feedback and recommendations for accuracy improvement. Rest assured, my experience in code review and optimization will ensure that your project serves its purpose effectively. Javvad Yousuf PhD Scholar | Lecturer | Research • Writing • Analysis

@muzafar042

Hi, I’m an experienced R and predictive-modeling specialist. I can thoroughly review your existing code for Firth’s CoxPH, Elastic Net, SVM, AFT, RSF, and boosting models, checking correctness, efficiency, clarity, data leakage, validation, and prediction performance. I’ll provide detailed feedback and practical recommendations while preserving your research methodology and making only justified changes. I understand the self-funded budget and can offer a focused, cost-effective review. Regards, Muzafar

@bizvivo

Greetings, With a robust background in statistics and data science, complemented by a prolific academic writing portfolio, I am well-equipped to tackle complex data-driven challenges. My expertise is rooted in the successful completion of numerous PhD-level thesis projects, where I employed advanced statistical methodologies to extract meaningful insights from diverse datasets. My professional journey has been marked by collaborations with various companies, leading to projects that demanded high-level quantitative analysis and data interpretation. These projects enabled me to delve into trend analysis, temporal behaviour studies, and comparative assessments of data variables. I possess proficiency in a suite of analytical tools, including SPSS, R, Python, OpenCV, WEKA, Tableau, Power BI, and Excel. My skill set extends to sophisticated techniques such as image processing, machine learning, deep learning, artificial intelligence, natural language processing, hypothesis testing, forecasting, T-tests, and ANOVA, among others. I am eager to engage in discussions that leverage my comprehensive skill set to provide innovative solutions in AI and ML domains. Warm regards, Radhika

@soniayousuf

I can review your R code for the random forest and related predictive models, focusing on whether the code is correctly built to support accurate predictions and clear analysis. I will look closely at efficiency, logic, and model implementation so your outlined methods are applied in a way that matches the research purpose and strengthens the results. I will provide research-based, practical feedback on structure, model setup, and any issues affecting prediction quality, with clear recommendations for improvement. I can also check readability, coding clarity, and consistency with your stated methods, and I’m available to work around UK time for smooth communication. Is there any specific package or validation approach you want me to prioritise? Best, Sonia

@TheSecondSource

Good day! We’re a team of 62 professionals with 9 years of experience and 450+ completed projects. Our focus is reliable statistical programming, predictive modeling, and rigorous code review. We can review your R models with attention to methodology, implementation accuracy, and prediction performance. We’ll audit the existing code → validate model implementation → check Firth’s coxph, Enet, SVM, AFT, RSF and boosting workflows → identify errors or inefficiencies → recommend clear improvements and optimization steps. Could you share the R code and project methodology so we can assess the review scope?

@Microlent

Hello, I am Dr. Rajesh Rolen, PhD in Computer Science & Engineering, with experience of over 20+ years in Data Visualization As a preferred freelancer in the top 1%, I have done 400+ projects here on freelancer.com, I have 4.9 ratings out of 5 on average, which showcases my quality of work and timely delivery. Key Highlights: - Free Hosting Support on the Cloud or any desired platform. - Free 3 months of post-delivery support to ensure that our client doesn’t face any challenges after the launch of the project. - Free Dedicated tester on projects to ensure quality delivery, so clients don’t need to act as a tester. - 10+ Years experience UI/UX team to ensure intuitive UI. Portfolio: https://www.freelancer.com/u/Microlent Please open the chat and send me a message, so we can have a more detailed discussion about the project to give you the project timeline and cost. Thank you for considering my services. I look forward to engaging in a productive conversation and understanding how I can be of assistance in bringing your project to life. Regards Rajesh Rolen

@kafupeople

Hi I’ll review the R code model by model to make sure the implementation actually matches the intended predictive methods, with particular attention to the accuracy of the code itself rather than just whether it runs. For the Cox/Firth, elastic net, SVM, AFT, RSF and boosting workflows, I’ll check preprocessing, train/validation separation, feature handling, model parameters, prediction logic and evaluation metrics. I’ll also look for leakage, inconsistent transformations or validation choices that could make the reported accuracy misleading. You’ll receive corrected code where changes are needed, plus clear comments explaining what I changed, why it matters, and any recommendations that could improve prediction accuracy or make the analysis easier to reproduce. If you share the R scripts and the drafted methods, I can start by checking whether each model implementation matches the methodology you intended. Thanks, Belal