Bankruptcy-Prediction
所属分类：数据挖掘/数据仓库
开发工具：Python
文件大小：0KB
下载次数：2
上传日期：2023-01-06 01:28:57
上 传 者：
sh-1993
说明： 使用数据挖掘技术，使用每个记录具有250条记录和6个标称属性的数据来预测组织是否容易破产。使用的机器学习技术：线性和非线性SVM、决策树分类器、高斯朴素贝叶斯。
(Using data mining techniques to predict if the organization is prone to bankruptcy using the data with 250 records and 6 nominal attributes per record. Machine learning techniques used: Linear and non-linear SVM, Decision Tree Classifier, Gaussian Naive Bayes.)
文件列表:
Dataset/ (0, 2023-01-05)
Dataset/Qualitative_Bankruptcy.data.txt (3893, 2023-01-05)
main.py (6948, 2023-01-05)
poetry.lock (17615, 2023-01-05)
pyproject.toml (314, 2023-01-05)
# Bankruptcy-Prediction
The Bankruptcy Prediction project is a machine learning project that aims to predict if an organization is likely to go bankrupt based on a set of attributes related to the organization's financial data. The project used a data set of 250 records, each with 6 nominal attributes, to train and test machine learning models. The machine learning techniques used in this project included Linear and Non-Linear Support Vector Machines (SVM), Decision Tree Classifier, and Gaussian Naive Bayes. The goal of the project was to develop a model that could accurately predict bankruptcy based on the financial data provided.
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