使用逻辑回归将https:archive.ics.uci.edu数据集17乳腺+癌症+威斯康星+诊断数据集分类为恶性或良性
Classifying the https: archive.ics.uci.edu dataset 17 breast+cancer+wisconsin+diagnostic dataset as Malignant or Benign using logistic regression (2024-05-08, Jupyter Notebook, 0KB, 下载0次)
使用细针抽吸试验患者的数据集，采用三种不同的方法来诊断乳腺癌：基于规则的分类器、随机森林分类器和高斯朴素贝叶斯分类器。
Diagnosis of breast cancer using a dataset of patients tested with a fine needle aspirate, employing three different approaches: a rule-based classifier, a Random Forest classifier, and a Gaussian Naive Bayes classifier. (2024-04-14, Jupyter Notebook, 0KB, 下载0次)
蛋白质图构造器：通过残基模板匹配将PDB 3-D结构数据清理和重新格式化为图结构数据的管道。2022年夏季在德克萨斯大学医学博士安德森癌症中心肿瘤数据科学研究所完成。
Protein Graph Constructor: Pipeline to clean and reformat PDB 3-D structural data to graph-structured data via residue template matching. Completed Summer 2022 at the University of Texas M.D. Anderson Cancer Center, Institute for Data Science in Oncology. (2024-04-02, Jupyter Notebook, 0KB, 下载0次)
该存储库包含Mohammed J.Zaki博士和伦斯勒理工学院教授的生物信息学CSCI4969-6969机器学习课程的作业解决方案的实现。
This repository contains implementations of solutions to assignments for the course CSCI4969-6969 Machine Learning in Bioinformatics taught by Dr. Mohammed J. Zaki and Rensselaer Polytechnic Institute. (2024-03-19, Jupyter Notebook, 0KB, 下载0次)
我们在开发三个不同的模型时使用了朴素贝叶斯分类器，每个模型应用于不同的数据集：一个与药物数据相关，另一个涉及癌症患者信息，第三个处理垃圾邮件帽分类。对于相应的数据集，实现的准确率为94%、90%和98%
We employed Naive Bayes Classifiers in the development of three distinct models, each applied to different datasets: one related to drug data, another involving cancer patient information, and a third dealing with spam hat classification. The achieved accuracy rates were 94%, 90%, and 98% for the respective datasets (2024-02-19, Jupyter Notebook, 0KB, 下载0次)
该项目旨在分析从威斯康星州乳腺癌数据库（WBCD）获得的乳腺癌数据，以预测给定的癌症是恶性还是良性。
The project aims at analysing data on breast cancer obtained from Wisconsin Breast Cancer Database (WBCD) in order to predict whether a given instance of cancer is malignant or benign. (2024-02-16, Jupyter Notebook, 0KB, 下载0次)
零售店预测预测罗斯曼在欧洲3000多家药店的每日销售额。利用历史销售数据和其他门店信息，我们的项目通过保留零销售额的行，实现了惊人的98%的准确性。探索了各种算法，包括Random Forest、Adaboost和XGBoost。
Retail Store Prediction Forecasting daily sales for Rossmann s 3,000+ drug stores across Europe. Leveraging historical sales data and additional store information, our project achieved a remarkable 98% accuracy by retaining rows with zero sales. Explored various algorithms, including Random Forest, Adaboost, and XGBoost. (2024-02-01, Jupyter Notebook, 0KB, 下载0次)
威斯康星-麦迪逊乳腺癌诊断问题作为一个模式分类问题。采用KNN算法作为非参数分类...，
Wisconsin-Madison Breast Cancer diagnosis problem as a pattern classification problem. The KNN algorithm is used as the nonparametric classifier. The KNN algorithm assigns the class label of the new datum based on the class label that most of the K-closest training data possess. (2023-08-09, Jupyter Notebook, 0KB, 下载0次)
使用不同的技术（包括回归模型、相关性、条形图......）对巴基斯坦最近的Covid数据集进行数据分析，...，
Data Analysis done on recent Covid Dataset from Pakistan using different techniques including Regression models, Correlation, Bar Charts, Histograms, Pie Charts, Scatter Plotting and Hypothesis Testing. All done on Python3 using Jupyter Notebook (Anaconda). A fourth semester project for Probability and Statistics course of FAST NUCES. (2022-05-25, Jupyter Notebook, 0KB, 下载0次)
使用威斯康星数据集进行乳腺癌的探索性数据分析、聚类和诊断，可在[https:ftp.cs.wisc.edu ma...]（https:ftp.cs.wisco.edu math prog cpo-数据集机器学习癌症WDBC）上获得，
Exploratory Data analysis, Clustering and diagnosis of Breast Cancer using the Wisconsin Dataset availabile at https://ftp.cs.wisc.edu/math-prog/cpo-dataset/machine-learn/cancer/WDBC/ (2022-03-13, Jupyter Notebook, 0KB, 下载0次)
在刘易斯系统生物学实验室（Lewis Lab for Systems Biology）担任研究助理期间，作为药物发现ML研究项目的一部分创建的笔记本电脑...，
Notebooks created as part of drug discovery ML research project during time as research associate at the Lewis Lab for Systems Biology and Cell Engineering (2019-05-20, Jupyter Notebook, 0KB, 下载0次)
单细胞RNA-seq数据由于其脱落特性，很难用经典方法降维...
Single-cell RNA-seq data are difficult to reduce dimension by using classical methods because of the dropout characteristics. Dropout is an event in which a transcript is not detected in the seqyencing data owning to a failyre to capture it. Pierson and Yau (2015) present the Zero-Inflated Factor Analysis(ZIFA) to analyze zero-inflated single-ce... (2019-05-09, Jupyter Notebook, 215KB, 下载0次)
这是尼日利亚拉各斯大学Onuoha Augusta Chioma的硕士研究项目。T...
This is a masters degree research project by Onuoha Augusta Chioma carried out at the University of Lagos, NIgeria. The project aimed at using DNA extracts from various tooth kept under different conditions to determines a person s Age and sex. I collaboratively handle the various hypothetical tests and machine learning model building (2020-01-06, Jupyter Notebook, 2965KB, 下载0次)
使用SVM-Bayesian岭多项式回归进行的19岁人群预测和可视化，使用SVM-贝叶斯岭多项式回归对19岁人群进行预测和可视化
Covid-19-Prediction-and-Visualization-using-SVM-Bayesian-Ridge-Polynomial-Regression,Covid-19 Prediction and Visualization using SVM-Bayesian Ridge-Polynomial Regression (2023-05-14, Jupyter Notebook, 790KB, 下载0次)
Covid19_Data_Analysis_Using_Python，这个由约翰霍普金斯大学发布的Covid19数据集由与...
This COVID19 dataset, published by John Hopkins University, consists of the data related to the cumulative number of confirmed cases, per day, in each country. Also, there is another dataset consisting of various life factors, scored by the people living in each country around the globe. By merging these two datasets, the relationship between (2023-05-14, Jupyter Notebook, 172KB, 下载0次)
阿尔伯特·伊恩斯坦-新冠肺炎（albert-einstein-COVID-19-challenge），提交HIAE Kaggle的新冠肺炎挑战赛（130多件作品中6名决赛选手之一）
albert-einstein-COVID-19-challenge,Submission for HIAE Kaggle s COVID-19 Challenge (1 of the 6 finalists among more than 130 works) (2023-05-14, Jupyter Notebook, 3359KB, 下载0次)
网络搜索报道19-康帕斯新闻，新冠肺炎是由一种新型冠状病毒引起的疾病。CO代表电晕，VI代表病毒，D代表疾病...
COVID-19 is a disease caused by a new strain of coronavirus. CO stands for corona, VI for virus, and D for disease. Formerly, this disease was referred to as 2019 novel coronavirus or 2019-nCoV . In Indonesia, for making data analysis, we should collected the daily data, which is limited. So, this program will update the data automatica... (2023-05-14, Jupyter Notebook, 133KB, 下载0次)
CoViD-19风险分析，遗传SEIR模型使用约翰·霍普金斯CSSE的冠状病毒新冠肺炎全球病例进行训练。目标是分析...
Genetic SEIR model trained using the Coronavirus COVID-19 Global Cases by Johns Hopkins CSSE. The goal is to analyze the evolution of the pandemic in different countries and assess the effectiveness of the lock-down measures (2023-05-14, Jupyter Notebook, 181KB, 下载0次)
法罗尔冠状病毒。费拉门塔·德·蒙托马多·里斯科·德科拉普索（risco de colapso）没有姐妹会（sisterma de sau de em municípios brasileiros com a Covid-19号Mo...
????. Ferramenta de monitoramento do risco de colapso no sistema de saúde em municípios brasileiros com a Covid-19 ? Monitoring tool & simulation of the risk of collapse in Brazilian municipalities health system due to Covid-19 (2023-05-14, Jupyter Notebook, 3407KB, 下载0次)
阿姆斯特丹本科系统生物学课程的Systems_Biology_FBA_tutorial、Python、建模和通量平衡分析教程
Systems_Biology_FBA_tutorial,Python, modeling and Flux balance analysis tutorials for the undergraduate Systems Biology course in Amsterdam (2019-06-30, Jupyter Notebook, 28470KB, 下载0次)