MCPcopy Index your code
hub / github.com/Giyn/DataMiningVisualizationSystem

github.com/Giyn/DataMiningVisualizationSystem @1.0

Chat with this repo
repository ↗ · DeepWiki ↗ · release 1.0 ↗ · + Follow
1,195 symbols 3,110 edges 30 files 42 documented · 4% updated 5y ago1.0 · 2020-08-02★ 1101 open issues
What it actually does AI analysis from the code graph — generated when you open this
loading…
README

DataMiningVisualizationSystem

:scroll: Introduction

🌀 数据挖掘可视化系统(Data Mining Visualization System)通过数据挖掘理论、机器学习算法以及数据可视化等信息技术,并基于 Flask 框架搭建 Web 服务器,实现数据挖掘可视化。

后台技术:Flask

前端技术:HTML、JS、CSS、Echarts

:arrow_right_hook: Instruction

配置完 Python 虚拟环境后,修改 .\js\DMVSystem.js 文件中的 var serverAddress 为本机地址后,运行 .\App\main.py,接着打开 DMVSystem.html 文件,即可进行本地测试。

:sparkle: Features

1. 系统主界面

进入系统主界面,系统提供 6 个数据集,用户可以选择导入其中 1 个数据集。

系统主界面.png

2. 导入数据集

选择导入数据集后,静候片刻,数据集即加载完毕。

导入数据集.png

3. 原始数据可视化

进入可视化模块,系统以平行坐标图、RadViz图、Andrew图等多种方式将原始多维数据可视化。

可视化界面1.png

可视化界面2.png

4. 原始数据集表格展示

下拉页面可以看到原始数据的表格展示,用户可点击数据预处理并进行训练。

原始数据集表格展示.png

5. 模型训练及数据挖掘结果可视化

静候片刻,即出现模型训练及数据挖掘的可视化结果。

模型训练及数据挖掘结果可视化.png

Core symbols most depended-on inside this repo

transform
called by 11
MachineLearningAlgorithm/Bayes/TextAnalyzer.py
fit
called by 9
MachineLearningAlgorithm/KNN/KNN.py
DataFrame2NPArray
called by 8
App/utils.py
predict
called by 6
model_assessment/clf.py
predict
called by 6
MachineLearningAlgorithm/LinearRegression/ML/LinearRegression.py
train_test_split
called by 5
MachineLearningAlgorithm/LinearRegression/ML/model_selection.py
fit
called by 5
MachineLearningAlgorithm/LinearRegression/ML/LinearRegression.py
dropColumns
called by 4
App/utils.py

Shape

Function 1,099
Method 79
Class 11
Route 6

Languages

TypeScript87%
Python13%

Modules by API surface

echarts/echarts.min.js1,017 symbols
js/DMVSystem.js25 symbols
MachineLearningAlgorithm/ClassificationAndRegressionTree/CART.py17 symbols
model_assessment/clf.py14 symbols
MachineLearningAlgorithm/LinearRegression/ML/MultipleLinearRegression.py14 symbols
App/main.py13 symbols
MachineLearningAlgorithm/LogisticRegression/ML/LogisticRegression.py12 symbols
MachineLearningAlgorithm/SupportVectorMachine/SupportVectorMachine.py10 symbols
model_assessment/reg.py8 symbols
MachineLearningAlgorithm/LinearRegression/ML/LinearRegression.py7 symbols
App/utils.py7 symbols
MachineLearningAlgorithm/KNN/KNN.py6 symbols

For agents

$ claude mcp add DataMiningVisualizationSystem \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact