该存储库使用乳腺癌数据集对CART决策树和朴素贝叶斯算法进行了比较分析。它包括Python代码、数据集、ROC可视化和预测癌症发生的指南，以简洁、有效的方式突出每个算法的有效性。
This repository offers a comparative analysis of CART Decision Tree and Naive Bayes algorithms using the breast cancer dataset. It includes Python code, dataset, ROC visualizations, and a guide for predicting cancer occurrences, highlighting the effectiveness of each algorithm in a concise, impactful manner. (2024-03-06, Python, 0KB, 下载0次)
布雷斯特癌症预测，，
Brest-Cancer-Prediction,, (2023-08-16, Python, 0KB, 下载0次)
在威斯康星州乳腺癌数据集上，使用Logistic回归分类器和Newton方法对患者进行分类...
I used Logistic Regression classifier with Newtons method on Wisconsin breast cancer data set to classify the patients as malignant and benign and predict with the model. (2022-01-01, Python, 121KB, 下载0次)
威斯康星乳腺癌（诊断）数据集，用于预测癌症是良性还是恶性。
Breast Cancer Wisconsin (Diagnostic) Data Set to Predict whether the cancer is benign or malignant. (2022-07-09, Python, 3KB, 下载0次)
利用威斯康星乳腺癌（诊断）数据集的数据预测乳腺癌
Predicting Breast Cancer Using data from Breast Cancer Wisconsin (Diagnostic) Data Set (2020-12-06, Python, 4944KB, 下载0次)
使用UCI报告上托管的威斯康星（诊断）数据集将乳腺肿瘤分类为恶性或良性...
Classification of breast tumours as malignant or benign using the Wisconsin (Diagnostic) Data Set hosted on UCI repository (2018-01-04, Python, 49KB, 下载0次)
预测癌症是良性还是恶性。癌症威斯康星（诊断）数据集。
Predict whether the cancer is benign or malignant. Cancer Wisconsin (Diagnostic) Data Set. (2022-09-30, Python, 6429KB, 下载0次)
使用威斯康星乳腺癌（原始）数据集上的分类算法来声明条件是否...
Using a classification algorithm on the Breast Cancer Wisconsin (Original) Data Set to declare whether the condition is Benign or Malignant. (2021-11-04, Python, 9KB, 下载0次)